{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## 随机森林 Random Forest\n",
    "\n",
    "> 从市场营销到医疗保健保险，既可以用来做市场营销模拟的建模，统计客户来源，保留和流失，也可用来预测疾病的风险和病患者的易感性\n",
    "\n",
    "随机森林就是通过集成学习的思想将多棵树集成的一种算法，它的基本单元是决策树，而它的本质属于机器学习的一大分支——集成学习（Ensemble Learning）方法\n",
    "\n",
    "随机森林的特点\n",
    "* 具有极好的准确率/It is unexcelled in accuracy among current algorithms；\n",
    "* 能够有效地运行在大数据集上/It runs efficiently on large data bases；\n",
    "* 处理具有高维特征的输入样本，而且不需要降维/It can handle thousands of input variables without variable deletion；\n",
    "* 评估各个特征在分类问题上的重要性/It gives estimates of what variables are important in the classification；\n",
    "* 在生成过程中，能够获取到内部生成误差的一种无偏估计/It generates an internal unbiased estimate of the generalization error as the forest building progresses；\n",
    "* 对于缺省值问题也能够获得很好得结果/It has an\n",
    "\n",
    "[随机森林](https://blog.csdn.net/yangyin007/article/details/82385967)\n",
    "[sklearn文档-随机森林](https://scikit-learn.org/dev/modules/ensemble.html)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DecisionTree with features [0, 1] has a score of 0.9266666666666666\n",
      "RandomForest with 30 estimators with features [0, 1] has a score of 0.9266666666666666\n",
      "ExtraTrees with 30 estimators with features [0, 1] has a score of 0.9266666666666666\n",
      "AdaBoost with 30 estimators with features [0, 1] has a score of 0.8533333333333334\n",
      "DecisionTree with features [0, 2] has a score of 0.9933333333333333\n",
      "RandomForest with 30 estimators with features [0, 2] has a score of 0.9933333333333333\n",
      "ExtraTrees with 30 estimators with features [0, 2] has a score of 0.9933333333333333\n",
      "AdaBoost with 30 estimators with features [0, 2] has a score of 0.9933333333333333\n",
      "DecisionTree with features [2, 3] has a score of 0.9933333333333333\n",
      "RandomForest with 30 estimators with features [2, 3] has a score of 0.9933333333333333\n",
      "ExtraTrees with 30 estimators with features [2, 3] has a score of 0.9933333333333333\n",
      "AdaBoost with 30 estimators with features [2, 3] has a score of 0.9933333333333333\n"
     ]
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 12 Axes>",
      "image/png": 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JKwOMBX4hIu8DDnXv4cdKqX+LyDeATwAp4F6gDRjj9hYfVkr9+C1h7m2CiPweeB64DXgAuBg4E9jPvaefAwcwsF7OBw4EKoBrlVLX7yTfo4HvA73AehF5ALgMUMAq4MtKKSUiP+F1OFZK/WZw/u9wfAi4D92ZOkNEfgbcAowDFvYfJCLHoJ+HBXQCpymlMoPyqgA2usfvrO0JA38G6t30c9Dv1e3u9QrAD4FTKHvmSqn73/K73t2W+s1YT+BK92F8z/27AXjG/f4cMNv9brr/3wwcjjYOV7hp4n4+7T4oA1gLVLrpjwB7A0cDL6MbzNHAgp2VDbgEuM79Pgu4383HBJ5FN4JXAp9wj9kbuGt387sTrruAJ4Bu4FtoI+F3f/8A8KcyTs93v/8A+Bq6Yr+CfkniQLub54ll500GXizL41z3+7XAb9zv5wPfcL9vBB53P+e9Tl7fd7+/H90YgjZ8i91nsQCIuemG+/87aYTRVcbF7UDQrVvXAd/Z2ftSXi/dvyPu/wFgDeAr+22d+//RwFL32Yv7TCvc334FfHg4HL+bPugO53iXvyeAkyi994cBm8p5dr//FPjkoPq8AG10Kth123M+cLF73pHAPeh25BlA+jke/MxH4vOOHWG4GIduvCtF5P1uWoX7f61SagWAUsoedN79wN4ichuwFW2d+1EHtCilugFE5HlgBtAKLHLzanodzfFZ9/+5wGzgMffvuFvmvYCjRORLbnphSHf79uJlpdRx7kjtp+gezjUi0ojuSSbKj3X/34Ie6U0ClimlCkCviKxyf5+By41SaoOIVJXl8Yr7/zZge9n3vd3vtlLq6P6DReS7r5FXP//9PD/u/h1Av2jnA78VER/aQD09FEL2ILyslDquPEFEbgJ+Box6jfOeLfv+ZRE5ET2yq3c/23dyzgKlVF5E6tAN0j/14I4ouqGL8e7keJdwFYLDgP5R2URgHvCi+/cL6FEYwBwRuRzNSwN6tAZl9VlETka/Yz9k523PDOBu97xn0Qa6Q0RuAG4VkRR65DfieMcaDBE5EN0g3IjuwfzKTfe7h7SJyEyl1CoRMZRSTtnpplLqh+7xfwTeV/ZbG9DgGoQe4GDg70AVpUrweug3UCvRDeHHlFJKRHzuy7cceE4p9Y9BZd7joJRaLCJNwBeAV5RSPxGRDwLfLD+s7Luge09zRMQCQkC/c8JqtPz3RxGZjB697CyPwfntDK+VVz//y4GHlFLngeZZKZUTkYVKqadFZCzwT2A/oLCTevKOgIiMAj4H/Ai4Av1scrz6/bbd46uAz6AbOR+ay13x3M9lO7AB+LBSqs/Nxwccz9A5frfgFOAnSqmrAUTkWOAPwP/Q7dEBlPi8EPih0hL6z9g5z53ojuqu2p7RaMnvEff/1S73tymlbhaRs4BvAFcxwm36O81g7Ccij6GH4O3A6ejh9O/cdNBDvG8DXwauExEFNLvH9uNoEfkBumefRfd+TgBQSjki8m3gIbRe+IDbaB493MIqpZaJyCPAEyJiA2kR+SjwY+BaEfk6ugLdD/xiuPm/jfgV8Ch6ZHUkuiHeJZSew7gN3dNag6vPojXfD4nI02iJ7utvokyvm5dS6j8icqjb+1XoEcvZ6F5ZLboeXeMefhdwv4g8oJT67Zso19uBfp0atBSRQ8uCz4vIX12D/iC6vt2NnhMqRzewAl3vV6Ln5V4Tbofnm8B97vyRg5YLh8PxuwVnojtQ/Xga/R5XiMgT6Hrfrxr8FbhRRFajjUD/CMMs48wHfO012p51wC0i8qR7/DnoEeFf3XbFD5wL7KDsmSuldupB92bQr3958ODBgwcPr4l3zDoMDx48ePCwe+EZDA8ePHjwMCR4BsODBw8ePAwJnsHw4MGDBw9DgmcwPHjw4MHDkLBHu9XGxFSjTB8AhbKldz4LHAfsMo95vw8KBXDKnL78fsjnSk79IvrcXL50jGGAaUC+bOlcuDbApnw1Tr50AcNvoByFKpQuYARMDKCQdQsnYAZMnKxNv/OZGGD4TeysXSyImIJYBk62dFOGpdP6Oje2K6XqhsvVW42YmGpMLI5jOxRS2WJ6oDJCIZ3DzvaTKARrouS6Uzi2vh8xDYKVEdIdffTftOm38EWCZLr6inlZIT/4fRR6kqULV8ZJGkESmZK7elVMyOQgndV5iUBVhUWizybvPg/DgMq4RXdPoVgHfD4hEjLpSRSKzyMYMPD7hN6+EveRsEHAb7C9acNu5z4mpqrDhz8exskVKGRyxd+CVVFyfRkct7KKCMHqKJmuJMrRddWwTPzxEJnOEs9mwIcV9JMt49kXDoBAPll6tlJVgcpmIVWKXKFqqujJ+8gUxL0m1FZCZy+4jxvLhHjMpKunVO/9fiEU0Nz3IxQ0ME2hL1niPhox8fsMtjet32O4D1REKGQG1fHqKLneFI7bEIlhEKwKke5M0X/Tht/CikfItfcU8zQjQcyQn1x7bzHNXx0jUBvFFystv+rrLdDZZdOXKtXx+lqL7h6bbM59h0yor/XR2pYvtn0Bv1BZYdHani9yHwkbBIMGHZ0l7iviJgA9vSXua6os/H5hw8ahc79HG4w6fNzQMAGA5h3aSFgWjB4F2Sy0tOrjggFoaBASfYrOTp0WjUJNtdDZpUi4a5KrKiEeE1paFRn3nWiohUAAmpq1wRGBD//8YD7w4HtJbekFWyGWEJ5QiZOzSW/rBQVG0CI8Ls7oyVWs+e96AKy4n2BDlGx7inyXvoC/JoS/OkS6KYGd1BUwODqKGfaR2tKDyjkgEBpXgRkweer20ze/LeS+DurFz19OOJlCKsf6+xagCg7BmihTPro/ia0dbHl0GTiK+KQ6xh8zl7alW2h5SfNQt9dEGvadxLanVtK9dgcIjDt0NhWTG9hw/wJSLQnEMphy/N5kxoxi++2PoXrTqHAQ55xP0pkJcMfLBrkCVIUVpxwbYUcb3P9CEkcJo+v9HHNEDWvWJnhpiW4YZ04Js/fMGAuW9rB+SwYBDtg7xqSxYR57vpPWjjymAcccXEVlhY8HnuggmbLx+4T3H1lDKGjyvR+estu5r8PHT2MzmHbSQaQ7Emx6YBHKdgg3VjL5g/vQtbaZ7U+vAgVVM0Yz5tAZ7FiwnvYlWwAYtf80amaPZfMjS0hs6QBDmHj0PCKjqlh370tku5MYPpPJ75uPacHa+5fipHIY8TDGOafBpm0U7nkUCjZqVB2F0z7M2nY/D6wJoIAZo4RjDrF4brnB4tXamM2fGWbO9CBPvJRkW3MWETh0/0pG1Qd45OkOunsKWKZw7OE1hILCg493kMk6BAMG7z+6Bp/P5AcXf2yP4P7nVbOZeuIBJLZ3suWRpeAoYhNqmXDsXrQv38qOF3TIt7q9JjBm30bWL95BYuFmEKHu6DlU7D2TrXc8SnZbJ2KZjD/rWPzjGtj4i3sodCcxIgFmfesUgnUVTD5rDlbQRyaR54n7d9C03eEPd/dh2zBlgsknTqpn0dI0/3m0G6XgoH0iHHdUJQ893s1Li5KIwAePq2T+nAh/uaedjVuymCaccXItYxr9XHdrC13dNsGAcM7Z9RgC19/aSjqjqKww+dInGzBN4ZQzThwy93u8JJVMQTKpjQXoRj2dgb6yTmkmC/m8oq/UqaKvT8fJGpxWKJSMhUKxLVEgkVYUXGOsFGx8ZAeFRB5sbbJVQWEn8+R7ssVRgpMpYGcL7FjaWsy/0JtDKUWht9Rry/dmUQWnaCwA8j1ZnExBGwtdEAqJ0jl7ApRS9G5qo3ttM6qgy5np6CPd1kvX6qbiUK53Yxt2Nk/XqlJ8wK7VTTgFWxsLAAWdq5tId/SRatHW2y7YbFixhcS6JlRvGgBJZZBlq1m5Q8i5z6MrJTS3O6zYksNRupfb1JojnbZZszFdvOb6zWkcpdi4NdN/SdZvzpDoK9Daobm3HVi/Jc2O1izJlO5p5fKKzdsHx4LbvcgnMvRt66B7TTPK7UqmdnST7UnRubqpWAe7VjejHEVnGfedq7aTT2W1sQBwFJ2rm0i2dJPt1i9NIV9g0+ptdG1sw0npRt/pTaHWbMJZubE4nJfmNmjtYEmLD+WGXFvdDAVbsWZTqT6v25Ihl3fY1qzrsFKwYXOazu483T36QRZsxcatKbY1Z8lk3fqULZ2zpyDblSTV0qPrs1vHE5vbKaRzA3le3YRyHBKvaEONUvQu20auvZfsNt1rVQWb7pfXk1y5lYLLfT6ZYcPTy4jPqMYKavUkGPNR0xDk2SXZ4qht/Wabnl6bl5ckiyOHhctSKKV4ZWmy/5IsXJKkq6fAxi2aR9uGRcuSbNiSpatbZ5bJKpauSLNsVZp0RmfW3WOzbuPw6/0ePcIALRftLK08XaQkLRWPMfWQ3TRLxsA09XEisF3l+C3b6E3bFNJwNvUc4YahClb6kcTAFfxiCWINSjMNfH6j7G8ppqsyeQZD9DpQVTpPBt3Y4L/3BFhBP062TKsTLW+YwdJQ2vCZiGlghnyQSLvn+RDDwAxY2O75VtCPGbDAEDY5aX7LdjLr1+FseJHPUc8BxABQkTAhv6IUQUERDAghf4l70wTLEoIBg56E5jkQMDBE8PuNYoMUCBj4fIJhlDocwYCWn8oRCOyZ3JtugwIghmD4TKwy7jXPghX0kcuVeDZ8JoZlFuUTK+jHCui8VpPmGrZjr1yPGMKXaGQuEZ1hOISEAsX8lSEQDBD2lWTYgE+/Q8GAFCXCgN/ANATLEgquRBgIGPh9A3kNBsxXcb3Hce/WcStUVsctzacV9JFz1SYr6AMRjJCvaHTNkB8j6NPvu2tsrEgQMxIEYDFJrqMJ48ENBJ76D3f/92cccsgclFLksjbRcKmOW5aW9SLhEj+RkIGIEA6b9Lr1PhwyCPgFyyzJ9uGQSTg0kNdI2MAw5FVpw8Ue9rRejUBAf8S9V9MEnw+CwdIxfr9biUOltJD7PVR2XCgIhiH4/fB7tvNdCnSjWIDiLlrZgh5ON+xThRHUjRtoQ2AELMxw6QU2AiZiCtWTKktpYZ82UmXHWRH9UhuhUpoZ8SE+A+l/oQTM8J5lu0WEcEMF0bHVRWMWqAzjjwWJja8utueRUVUYlklsXE3x3Ni4WsQQomOq3cwgNr4GXySAvyrMb9nOr7DpVorHHJs/s4M28qhgACaMYXwV+LTkSkUIKiPC+AYLHeUF6qp8+HwGY0eVXurR9fr7qLpS2ph6PwG/QXWF5tYwYFR9gMq4r/hC+Syhoab0bPYE+CIBgtVRYmNrELcOBmtjWCH/AJ6jYzW/A9LG1WL6LEINbgxOEWLjavBXhLFjfq5mO7fg0KUc/mHb/IEmEtgYsRAyug4mNJZ6XrU1EIswqaqAuL2dcTVgiDCm0Sxec3SdH9MU6mv8/ZdkVL2fSNgkHtPHmSY01PmprfIXDXbAb1BbtWeFUfPHw/jjIaLjqouNTrixEsM3uI7X6HdkaoNOEAhPqsOMBPH3c28ahKePIjimhr6oj+tp4t8oOh2b6xNJPvaB75BOZ8mlCvT15Jkz2VekfmyjQShoMG1SqQGb6n6fOrFk1KdNDhIKGoxu1DwaBkydGKS+1kdlXGfm9wuTxvuZMM5PwO14VcQMGuqGX+/3eIORSkOqNK+EbUMmo2WqfmSzWqpK7kySKjuuLwm5vMNT2V62kucrbvpM4DhgIxmUgk2PtmD35Yq9BGUrCskchd7SBKSTtXFyNi3LSpKUndCSVH6QJOUUHJxUaQhf6M1ipwuofLkkVcp7T0C/JNW1ZkdRFsl2pUi19dK1urk4WkpsaaeQzes0F51rtCTVs8HlRkHn6mb62nr5b0cTeexiYK/9gP0QbawzWWT5WlbtEPJub6knLTR3Oqzckke5ktSO9jyptM3asiH1hq0ZHKXYVCYvrd+aJtFn096le9+OAxu2ptnRliWV1veULyg2N+1Zskg+mSWxvZOutVpyAki39pLtSWk50EX3uh0oR9G1psR995om8sksye3uZJ7Sv3c3dfBgYgeVKD7oHnsUMBmhiRxOIo1auwW1clPRm0Ra26Gtg2VFSQrW7dCcrdtcGnlu2JYhm3NoailJUhu3aEmqvyds27B5W5ptO/SxANmcw7Yde5YcmOtJkWrtoXt1c7HR6dvWQSGdG8Bz15pmlOPQt2SrTlCQWL6dXHsvueZunWY79C7cSNvyjTzQ18wU9N4KAB8BYo7Dpk07CER8VDcEeW5prjiZvWmbQ3dPgYXLSg3YouVaklq8IlVKW5aiq8dmy3ZXWnRg8YokGzdn6O7VmeVyiqWrMixflS5OoPckHNZvHn69f9MGQ0TGid42dYWILHc3zhl8zNEi0iMii9zPxUPN3zLBHNT5tqyBaSJgmDq9/BgRPVQDyOGgDIcrupp4hB0E0RHCQO/wsgCoQVvcSH0Qw1fqQYGWXozyIbZoGSkQL1l7sfSQsfw4wzJ0L7FsOGhYBoY1kPrBfw8FI829PxrEHysbohmCLxzAHy2lmQGf9swpS/NHg4hpFIf1WRwI+/jO84/yMi2k0ZHvQG/ssBxFjauOqooYsWBJAhEUkaAQLxti+yzB5xOikdIzioRMDBFCQWNAWiCgPXPK08Lhgc82Ehr491Aw8twP5NmwDKygD1+sNIz2RYKIIfjKjvNFg5h+C8Ov+cziYIcszn/hUdbQzg4Um9xjm4GNKKr7lemKKBKLFPNSpgnhMPFgyVsw7NfvZDQ0kFPLEvxlsmEkbBIKGkVlALRUMpjrPY570XXcFyuv4xaGz3wVz2IYmPHS87DiIcxwAHHf5QwOmbDF+Q/+gyY6WYeiv3u5AWjN2zQ0VKEcRSZlUx0v1d2AX3uVVcZLjVpl3EREiqM20N5PoaD2/CulWcRj5gDuK+MmlfGBXFfEhs/9W6GDFIALlFILRSQGvCwiD/fvRVGGp5RSHx5u5n53xCqiDb7pGoZgoBT20efKhv6AHpGAlrEAsn6bqwrbWU4GIwu16If1X/SWWfOBjSJMVVHmEEIEqqfHMJrM0ryDqY2ACpYINnwGYgrx0THaVusJRiOgfzeCVtFl1ghpScoMmNjpgptmaeNiGXpCWUCCw394jCD3IkKgKoIRsNw5GQd/NIgV8hNurCxOAIZqohimQbihguSObgDCDRWICKmqID9Lr2E9OYyN6xmPNhR/Re8CMx9YZVkcSAUTC0FUwAeNdTTmwTKg4EA0qBunUbUmSzYoFEJl3MIyhfoai6YW3bOqrbLc/31sSeueU12VH59PiEdNunoK2iW0ykc0bBJyNXjLFKor39BrMGLcWyE//liIcENFsQ76K8KYfh+Rhgp6N+pmJ1wX1/83VJDt0j3RcGMFYhl0x01+0b6WreSxVq9nJnqzht+jt9mbDyw1TT5ANXW2D4kEkZpKVKKvpMFXxSEUZEzMZmWrBQj1Fbpu1NUYtHc7Ls8mpiFUVfhoaXOfR7WfYMAkEjbpS9oYBtRU+QgHTfw+IZdX+H1CRWzP4t4fDeKLBAg3VNK5Qm8PEqyOYlimruNNXZrnei07BcZWkVqhG53gqErMkJ+muMlvOtfRQoHAMxs4EHgYHXd+HrC3CIt8Fj/5+Zeoro6TTeVJJwtMGWvy2ALdztVVG/j9woTRftZs0KOwfgl27Cg/Xd36muNG+wkGhNoai6YdeUR0WlWFRTRikOhz8FnC6AY/YlDkPhYxqKoYPvdveoShlGpWSi10vyfQ4ZLHvNl8+5FKaU+pwZJUudSUy2lJKlWWlkxqWeXaVDMHkSGNjrMNOk73R9AjjMeBKsNPDoet5FAKtj7VRqGvbAGHrSik8tpzyoWTc3ByNq2r2otpdjKvvaTK5KVCQktS/cZCp+WwM4Wi9xEK7L6yxSFDxEhyr5QisaWDnvUtRUkq15sm3Z4oeT8BfU1dFDJ5ute3FNO617fgFGx+3bSME8mRBhYrRadSLEDHhv4v8CTQGIrRW8iygxySzSOr1rOmVeinJpERWjodVm/JF2WRts486bTDhi2lIfXm7VkcpdhaJi9t2q4lqS7XU0cp2NyUoaU9V5ywLdiKrW/AU2ckuS+kc/Q1d9G9rqVYBzMdfWR7UnSvK3Hfs6kV5Tj0rCvjfl0LhVSWX7Sv4kvkyQDPKMVGpVgFfBW9JeGzwNhAmFY7Qwd5VDKDWr8VtXpzUYqV9i4Kre2scI0FwKY2SGcLbNhaqq+bmnJkc07RWICWn7p68sU1F44DW7ZnaGrJksvr/HN5VZSxhoOR5D6XSJNq66WnjOdkczf5VHYAzz3rW3Bsh9SKkkTYt7qZVGs3V3Wu4hIKZID/OA4vOw7b0Rtj/BR4SQxmTh7L0lfW0traRSDso6ouwEvLS2sptu1w6Om1WbyyJD8tW6UlqeWrS96BS1em6ewu0LQj73IDS1em2LQtS6KvJLuuWJNi5Zp0kftE0mHT1t0gSZVDRCYC+1BSe8pxiIgsFpEHRGTOa+TxBRFZICILEtj4fHpRXjmsQWmGUZoM74fPp3tCq8lwIXrDhGr0dnDfAhahd5kZA3zHzvJRkvyULTSRIz4ujOHfiSRV7l1jaJkgXF0akorPlaTKzjX8JmJI0YOqP83wGQO2Uhl8veFiJLgPVIYJVJYkCjEN/LHggDQr7Mf0mwQqw8W0QGUYMQ1Wutwb6JHdWPSmFavQ27FNBr6X6OI4+vgxW3TDVVtNdaRscaQoYhGhKlY+XBf8AYN4tERgLGJg2zkikdJx0YhgWXl8ZR2pSAhCQWeQVKLIF974PMab5X4w7wgE4uEBnBp+C1/YP4B7fzyEGMaA44KVYXKmsJU8F6CrWD16C7yvoDcm+QF63u77qQQHkuBytpDAxq6vwK6NF/NSPgu7IkZlpCRJRYMKXwAqY+XcCyYZgoFSWjQCAX8eo+yViUYUkfDAzS8jYRvbTvNG8VZzL6aBPzqojof8mAHfq+q4YRpY1aXjfFURegwbG4fPorkfhd639svorT0vB+Yph/NXbSRw60Mctf8X6e1Nkeor0FBTIisU1B5QdWUOGTXV2qmmpqpUoWurLaJhcwD3tdUW1ZXWAO5rq33UVpfOMwyorhr+COMtc80RkSh6G8HzlVK9g35eCExQSvW5m7vcC0zbWT5Kb0Z/PcBkCSprUAn73WfL003XVbbcYPT/XiMmzyqH49EbbNdT2r7KQO9Ucqh7TguKZ+jhM2PDGBvLJCnDnZ8om9cQ96LlBqN/3sPwGzgZ3Uunv3NmUdy7THxGyd3W7l8l+sYNxohwb4SULxpERIp6oBXyY/p9BKvKGq2o22hVhOlz/c8DFWFdsQ2LZ50C09Fv9BT0vp77oXeHeYXSVnzrcHjeSPH+qjjVdkkVCfog6BeqYwb6YejV26bBQIMR92H6g8SjafqSWZRSxOM+AqEQwUAfeXfIUlkZJBL14/f1kc0pDAMqKkKY/jf2KrwV3A+u86Zfu3WWN1q+cADDZw7gPlChvwcqw6Tb9foWf2WEkN9HAIOFOPiAI9B7BefRW1RmgCb0u3AysAyHRb4MR1dGsOvqUCKIUjixCE40qr1t3A53PCpgBolXOLR06BFFRaUF4TDhqEMmm0Mph0hlCDMWxe/vI5NRiECkOkYgZGJZKQoFhWUJgco4dnAP4j7owwz6BnIf1XNFgcowia0dLs/aePhqohQ6tbThr44QjMdIorcwbEZver4/mr5Z6N3aFipFDDgpb7Oou4//PfQyMSYxqtYoNjkVMQPLkgGNfG21biNqqi3aOvSoubbG0rJr3CTTVgAcamtMwiEhEIB0Wnemq1wD0u9+GwwYb8it9i0xGKK3C7wbuF0pdc/g38sfprtD1+9FpFYp1T742MFIpwfu1+k42isqVdYpyRdcL6nUwPMe7uuhSeU5Hb2l1bHAv9GG4kbgArSWXgdcR2m4te3ZNgrJMknKATudxy7zdFJ5Bydv0762s5hmp/IoR1Hoy7Nj+yPsaHoQpfKIEUc5Xfj9Y5k8/WzMvonauNilOyskcphv4MUZMe6Vom9bB9mekh6Y78uQ7kjQs7HkGZZq7aGQydG7qa2Y1ru5nSfiS+hzCrwPvUfrx9Cbggt64+krgDnoEd7N6BEgjo2s3cS62PxieI9UTmjuzLC2CfqHZJ09BfqSabY2l2S+7c0Z1Lws23dk2L71ftpbHmPRSzamGcG2ewgEJzF5+tlsa/Lj2IWit4jjQFNzknikzCd7iBgp7u1snuSO7mLjBJDtTpLtSQ/gPrGlHeU49G4qZde7sZW78i04OByANtCfQ2+ZCPAd9Abbo9AjvNvQ9d7JF3A2taLWbkPc52129kB7kg1tpcazqR3ymGzZXhqRbdmeZ9IUh472NFs33UtH+9MsXgAiARwnSSg8jcnTz6ZpW4BY1Cyu1SgUFK3NPUycWOZYMUSMFPeFZJZ0W4LeTSWe0229FNI5esrr+KZ2nIPHkV5bkqmS61q4oW0TCsUsIA58Hy1FKfRz+CtQCcwG7kBzb/oNqioCvPLPVLHJ2dHm0JOwWbG21NCtWpdBKcWa9SXPslVrM8yaFmJHS5rN6/9Gd9dLLHrJQMSH46QIR+cwedqZrNkQwxAprtVIpR22bM8xa9rw6v1b4SUl6PZ3pVLql7s4ptE9rn8vboMhbAsJetI7MMhV2+cbmNYvSZWnmabNVZ07+AF6/8oTgWMo3fBh7v8Z4B7gU+h9JA8hTvW0OEZgYONt+i298Kx4UcGwDKINZZKNKz/19C6ipXkpSq0EulHOkcBXyOV+xNpVN4DP1iOKcknqDUx6jzT3wZoYoTKJwvDpOEWh2lgxzRfTXjnlaXZlgKtfeo5foHu1h6NdOPtv93C0Ac8Cf0L3cv+OcCAxVGMdDbGSIbUMRVU8Qn2Zv34oaBAIhamqLA0pqyr9KCtEsvc5Olq3o9RGoBXb3he4kGzmXNat+iMVlX5ileEBw/WKqhCOObxGayS5F0MIVkUGcGoGffgigQFpweqojmlUltYRt7h9xRJuQnM/C819P44EYuh34qfA+4GngH0kijOqhvyo6uKxTjBArjJETdnziEcEhUlVmZwRjVuoYIz2tsfp7MiCakapbTjObODnpFOnsX71n4lWRQlXxUoVQSBcFSNvlso/FIwk94ZlEqgID6zjkQBmwDcgLVQTwzAN/PWl92NVqMADq5dxN5rfUejRnXurHAU0uL99Ezga2BwLceQRe9PVmWNs3UBJL+TPM6qu1C401lk4hRwNtVZZmkE4YNPa9AA93RVAB0qtx3HGAzeS6juKjev+SkON0FBbuk/TgJoKBzs/PCn2rRhhHIbew3epiCxy034AjAdQSl2L3jT9yyJSANLAJ9QQ94Y1TAYMMUTQAf3KpxMM6HIKLHAyCCZTCfAMCfLAd9EP63Dgl8An0Xr6legXxwIOQRsToZqxBAjEfQPmHBCKslTporowvqBFX2IDdiFJtGYyUEFv13oc52vABPfgHwJnAVejnMvIZtsISnyAJPUGV3qPIPeC6beK4QugtOLVLFsFa/p9tKRSvFTowSTNJAL8K91CmNKmxwcCv0aPMsLohqoazf1xaM+RKdRSawZwQkGCTkkNtFz5seyS+CxFoZDEZ+bo612LbWeorphKLhOiq3MDjvMtoNE9+kLgEuBJCvnLyGU6UAXRkhdufSJHLjNQWx8CRox7sQwMnzVwtbFPd0YGcB/0sT2RYIHdS4gM4wlwR88WRgOnusfMB34OHI/m9OfohsxEG+qLgWNpJO4LUvAHWDtqLzZNjlGd6WLrmGkcbMUJ+EtF9vsFFJiWTaJ3NY6Tp6Z+NllH6OncgHJ+jH66oMfwfwHuJpO+AltsHDNQlBsNAcc0SQ+b+pHjvt/lvZxnI9C/or5slX3Ix+aeXhaoPirJMgofd7ZtYh7aCIMeRVwJHITumP4amIrm/jPAxZbJjXdcTCQcwpYE8Qof2pxoycgIRAjHbHTXCsJhH/jDBIJd9PasBOXg883HDIbp7l6PUreiW7UYeovvp4BfkuprJBQLYYhgGL06Jp9P8EfCMEwp9k0bDKVU/wbor3XM1cDVbyT/zCBJSinIZXU8qX6sKqT5bfM25ivYDGQwsG0bBaxDC5fb0fLHRHRbvxfQv4IiD6xF+AC6l9n0cscA+QkFdqYwMK2gsHN5nv77L+hq3QYyBdb/lTnRc7GMECIvU6qer6AV4xaUasMohHX02jJJyk7mscpWiA8FI8u9ItncpSUpF4V0jkxnH31lUsmCjhauu3sx+9kOq1E4GNBjk6DEeTNQhW7CDfR8hrsWlhSwGeE4gojtIFs2szleiXLHgpmC0NmbZEtraeK1t0+R6Mvy8MPXk0ikQUazecPfmDjmayjCaPn6bPfofu43AWm6e0xCoUxxaK4UtLRmiA1zpf1Icu/kbFKtPQMkqXwiQy6RHsD9401buOWel9nfdliKwkDwJRw6gE50s92Cfslr3MIegGYDoBvYgTCBAOTyyJbtbM5PZ2XtzOI1ZudNtnXY9L+F7V0OyXyGRx/6DZmUBVSxZcNdjJ76UwwzDLwMxaWBi9yrLUckQE8X2I5dDNPiONDTbROrLvXSh4KR5L6QyZPuSAzgOdvZRyGdI7GtlPbvzeu5a/Nz7GsrXkFhIgT7HFqAJBCB4pqLSjR7B6LnT0HPafSaBrNmTcAXMKms9rNifWnlcXunQyJhs35D2eLUzWn6+hL8598/JZ+rBALcsvleJk28DMOIouv9we7R/fV+MaZZwYZNGcyyEDnZrGJ7U46Z04dX7/f4ld6BgF5z0Q8RLVOVhwb5Mzv4vVI8gmI5ilpsvoBuoGajvXOuQw8Be9AP62qgHfgEcKAIMULMc2Pq1M+tHBDHR8eXsXS8pP4kU+hqeYXu9gSOswrHfgTHuYXVz9xE46Tj8PkfxzCOBzkN+BoQwTD2p37UMQQrq7UkVbaYzwztWaFBQPuaRxori3+bAYtAZXhA2o3SzN/sAg/hsBJFAJuvoQ3ERHSX7x706KIb/RL9EFgPnCXC/pbFNIkxhSDKMEiMGU8kUtaTM8GKhKiuLlWCSEhYtepp+voqcJzlOPZj2PYvuO/+vzNz1vFYvjsQ48OInOxezUGMgxk97qM01EeprvQPiDtWW+3DNPec8CBiGYRqYgN4tsJ+/NEQYTfNRnEjLTxkF/gvDitQFHA4F90RakTPUTwFfB5tQDrQnlIvAJ8UYT/L4jAqaMQPfovsuFHUlS5J0A/hUIGGqpKxrogZPPXUw2RS03GcxTjOkxQK3+Wx+25k2qwPY5q/xTBORq9y+h1IF2Icw7hJp1BdH6GiOoT0R8QRqKge/tzRSMLwWwSrogO491eEsYK+YloKm9vtHTxt2/wXhyUoMjicjx4fVKM7qcuB76HbmW7gNOBfwGcMg4MCfr73g7Ooq6vEzjv0dueYMr5UByviBtGoyfixpXo/dkyAu+6+h1z2aBznZRznOXK5T/GPe//KzDkfxjAuQozTEDkWuBPYiBgnMmHySYwbE2DsmEDRO9BnCY0Nww/Lsue1UoNRFrQPYGeDylYKvMf9/hjQhp7k+xDaUPwZLUr8Eu2pMxo9+TcfeEEsPldZT6zLz1+tNvqMAv+8p8CSjavIZ5LE41NoHH0cpT6xWw4gm2zDcQ6nNFY5hnymFdMKMXPu+fR0LQG/Q6D606R3dBL0n0I0Pq14WwO1tjfEzsij3P/UjVjaX1YHRbuyOdr99T9AH/BjtPT3E+A3aON8Ebq/E0e71M4BXgmH+dj73suTy8bw09ZHSPgMql98mObmDroSeeIV0xk34VgCwRBmmSwiBiST3dj2eyhV4WNJ9H2XcKSSWXt9i56uJTQ2CBMnfJIFC7uwfGcTiU4iFDWJVloD+I5UWMT3sHhS/VQPTCghiY2g2M/9+270araL0fx+G20q/w6ch+7xCtqlfBqwtKKK75z5IaYfNIU/3nAvqirE1uf+x6pVzfRlFRUVM5kw8T040XpUIIMWVbR02tndh+N8gFJ/8z30dF7HhEl1zJr3LXq7l1I/uoHqhi+xevFWgsFzCEfG6aoj8iqJeY/Ea5SrG5tqEWa4jdFf3MMvAi5Dy03fAP6HNtbXo0fSlwGTgNWjR3PFl85g8nsm8KUvXkk2U2DbFptlK5rp7XOorJpLPHqMW47yqAfQ1NSGUicVC6jUsbS0PMDk6WOZNe8CertXsNecaTTUzeGxJ9sIRr5KKDTKlV6l1H7K66pzO8UebzCymYGSFOiFepkySaoWk99Q4AjgJLRyWod+YX6E9sr5GRCk9NDOAb4EhFWBcfj5pn8Lx3/UYcXLIZ5Y2Ah8GriXtvQqujqWMb/xYnqaV9LXvolYfCaR6ATC8YmI3Izie2jx5XeEK6biZGxMM0h17YGIzyA0Nk6q0F0sr50q6En1sg2g7FQBKzJ8iz+SSLX2DJCk7GyebHeSpBsrx0Cox+BqHOrRL8cP0Dxfgp7BuRCtmwfctHFu2knA6FQKFR7Pi1uv5WMnZ/nf/8IsXDwW7YLwFzLptXR3rWSfwy7m5UWvsKNpOxWV2rdq/NTJGMbtOM5X0LNSv6V+1GTaO2wsK0xN3cGE4ib1k6NUbOwp3sOW5gJppBhGGmBTs40R33O4VwWHdHuiyDNAIZUl15ch5a6mj6I377od3YO9CF3f82hf/2nAL9DGOuD+Phato+8HHJpIMGZmI6ecfyUf/WiG++4L09n5fvSyyhvIpFaR6F3P+47+BksWP09bewcVVfPopoEp08bz8os34ThnA1FErqFh7FSSiRw+X4yaukOprI4wfkoNbdu2FO+hqzVFLl7azEop6O7IEK0YvpfUSMHJFch0JQdwn+tJUcjki5EMarHoUA73oxdAXgNcih7FXQTMQHdOx7rnX4huHf6MrqlndXYRqA7w4Q9/k5NOynL3PWH6+k5B6x2/JZ1aTF9iM10nfpvnnn+Crq5uqqr3Zev2ambNmsySZdejnBMBC8P4PZMmTqSn18bvr6K2/jCqqsNMnhJm0YqSQ9jWbdkB8775POxoyVE5zNXee7zB6Jeeetx3XtwQII7Sq8ABerG5G/2QzkMbCdATTJ9Fjyba0b3bKvQyfRPtKx2wTDZ9ah6HrdnECSfDP+6z0H2DILqvMItCYQxLn7qCbF8PMJ1mHqF+9JFMP+qTzDjofax6bjoQwheIMfuoC1AJnw5eCJhhnxvt1iyGCzEjPkw32q1y5zHMyB7Ww0WIjKrCFwvRsWIbKL2AKVgVITq2mr7tnSgUnThcjR7VXYruwYL2BrkI/Qqk0X3RBjT3AjwHVPp8rF7/OCeflOWII+CeeyqA+9HV8mxgPLlsLX/708X0dieBKTRve4jJUz/I3nufwspX1rF21XggSDhSy8mnXsCypQYd7drdtr7eRyxoEA4bpFLaOjfUW1RXWMVQ3P07m1n2G+txjQQMn0m4Pg6K4spuX0zH9YqOrSbdniCHIoniB+hR3e/QXRzQjgVXoucrDPTynxnAP9zf7wcqIkFu+PsDnHZahsmT4c47xwF3oZ/OacAoUslafnX1xfQlCsA4mrY9xKx5p3Hg0Sew4IWNbF4/CvARr5zA+075EUue7SDRrXtyNY0RYpUB/EGz6FBQ2xghGPFhmIJjKwxTqKrbsyQpM2gRqDWJjIsV55AC1WGMcIHo2DhdKzP0uQuqzkGPu24BPuqe76BHeb+hxP1BwA3u77cAVRVRrr7pr5xzTha/H2x7PtqcAJwATCTR28V3v38uyaQJNNC09SGOOPKznHbqB3nqmd/QtL0OMBk9ejpf+uIF3HhrLx2dulyzpvuZNNEgGBQyGb3WaMY0vQ7jqef0PEYgIEyZZBAKDi/CxB4/h+Go0kQN6F6JcsCxYRMZLmMTaRT3oyeXbkD3bH/t/l1Ae0EJ+qXJoV0sznXTf/WrL/DkwrWEY9rqGkaAksRkAQq/fxG5ZBM6uMj/gKNobXqCp+/4Ahtfuc3VvwsEQ6OwApFiKA2gGP7DKd9P1lbufagBaXsWFE6+oLep7A/LUrBRjsLOFlhNmv9jIza68Q+gJajJaFfZSvTLdBi6kh2HnnZ+D3q19/uAiy84hZVtLUSjmnuRMKU+TADN/Vp6u1vQEcAeAPZnw7r7+dH3vsDWTQ8ihh9QRGJjCFXWDNhqt2CbiD9EoYzbvOPDsQLY/ZGIFdjixwiWVvHubji2g1NwKGRLL7OTt1FKc7+EJJewEUFPbQp6VD0NLUFVoufqXFGDzwPPoKeiv4w2B589/BBWbN5KJNLPfYySDhMGFIHAdvoSfegndx8wi5VL7uC7Xzib1ubHQXwgBtH4aHz+IIUy8vM5G9tW2AWnLM3BLigc93k4tsIu2wZ5T4BtO6QsH5nyepS3SfsDZPOKF+nlx2zGByx2f/802n35QfT8RTO62S+g3WfvQs/hnYOeQ/rS+WewfntTkXulKstKEAfyBIPdJJMGmvu7gPE89eQNfOzjn6W7awFgIWJRXTOWQCBMLleq4+ms4CiLQr601ihfMCkUzLKN6BSOsrB8wxtZvyUGQ0TeLyKrRWSdiHxvJ78HRORO9/cX3OX8Q0IuC9lBkb/zeWjP2vyKbXyfHBPRDdIo9ITe/egga6egHcyuRj/I96EnXeejX6wp86fgmCZrN67jgQdg1SqorEyhxaoXge9QW9vMVVcViMdt4CxEDgK2YFkTEJlCIW8SDqdR6hckuqey6qkbB+zV7eRsPYoo2wvczhRwcvYArc0ur6HDwEhyn25PkG4rLaBVeZtsT4qtO9r4Hdu4igJj0UZhFtpH42/oHtan0aO5W9FN/wFAAr2y+y/AIcfuS5MDKbuDv/0NWlogEGhGO0K/iMgXGTcuxc9+ViASyaNlqv2BXixrAjCZfF4IBTModR1tO2L8557b6O0u8djdbZMv+MllS0T39jikkiaqrJ1K9IIvUFpPM1SMGPeOItPZN4B7O5Mn35dlbXML19PE9dhUoaMUHAosAW5Cx4o6Dz3p/Q90ozUOXdXGoyWs+UR5af0mxNfHTTfpRa4iy9HLKV9A5CxmzhQuv9wmGEygn+b+gI3PNx6lplDIQ8CfQTm30rw1w+P//jPpZIn73s4MqUQOu6ze93Sm6e0aGM68t/uNhWQZMe7zDmbej91ZKqedyBLwx1m5o43baeE2V0s+HD1Puhz4LXAG8H9oZeMe9GjDj164Wo3m/gvfOJUHX3iZaDzNH/7QH53iMfQY8QUM42QOOMDPRRc5BAI70CrHQUAQn288jjMF21b4fFkc528sX7aNO/7+r2LcKIDtO/K0dqqiJyDA9pYC21tKCbYNLR0Ohv9tNhgiYqJlvA+gnZJOF5HZgw77HNCllJqKno/+6VDzD4UgXDZqNQztObXNl2Eciioohmv+KXpSey5aS++n5z60h8hPAbFM/mGZTN5/Bh8/4ziuu/4fnH12nhNPhL//HUwzhWHcisjx7LXXNfzhDynmzIEPfhDC4UdRahVVVSs455xVHHfcUkwzS319Hsu6A6V+QnfLQoywkOzbTFfHQtL5zSjyAxbmWTEfZsAasIOfFR2+JDWi3IveACk+oa44M+mLBgjWRNkYh/koHGALWhL5FXpktz+6V2W66XdT0tXFEO6xTPY+ch7vOX5/bv/bg3zuc3ne+1644w4IhVKIXA0cz4EH3sbvfpdi3jw4+mgIh+/DMLbQ0LCEL3xhNYcfvhTLKjB6dA64B6WuZPWyF6hu9NGX2EBX50IMfxOOr0Ckoiwez5gQoRofPnenN8MUKhqDJAvDG5qPJPdmQHvkxCfWFTv9gUq9sc+amMORKFrQnjct6KZmDLoB+yxaTN2ObqDCLveO6EZsCiEmmGGebt/CV79mc9hhcPvtEI2m0QbjvRxzzH1cdVWKffeF/fYTKir+jmW1MX78Er7whTXsv/8SDMNmzJgc8B8c58esX7mQWIVBX+96ujoXYvpbicR9BF1XcRGoHxOjpiGM6a5nMi2Dmobhj+xGkntfPEjFuCDVc+uLaeGxlYSrFCsrbT6AYgXaGGwE/oDuqB6PHlVUoyMy/wX9HK4CcobwL7/Fh089mrq6Sh545HnOP99h3jzNfSSSRrdY7+VDH3qMH/0ozcEHw7RpBtXVf8Hv72H69MV84QtrmDt3CUo5NDbmgUex7ctYuGARNTU2id41dHe+QnVVO+PHBYrh/y1TmD0zysyZESy3zYmEDSZNHL4c+FbMYRwIrFNKbQAQkb+iuSsPNXwCes4T9PjqahGRoSykKQzqeDsO2Lbiv6lu1qI4A91QtaDXXBzrHrcabd3TuIFigAbLR6ZWyGQKvLx0NVtbVtPaCitWQTQqiOh5kUAgjUiWk05yqKmBq66Cp56CmhoH24ZvfUtx6KEADt3dBi+9ZKKj8+wL4mfZcz8nm7aBHKzP4V8aYtrML+H3Vel7yDmokIMq6305eQdz+M9v5LhXinwqS643XQoNks6Rz+R4YOsG1qH7ndPRo7b16PUVoEOH+tAv1Y3oZUcNkSD5mE1fusCzLyxh3cYltLbCZZdBZaWeT8jlDPz+FIYhnHqqIhqFSy+FxYuhuhra2xU//CHMmgWnnOLwxS8arF3rQwszx2NaJk/991Jy2SDQy6Z1ioXPVDFh8jmI6zKdTRUQ2yGf7ZcKFXbWJugfdt9pxLi3s3kKmRy5nlRxFJpPZsllczzSvJkWdJTl8S73GygtEV2FNtYWWi9PAWMiQaTCpruvwOp8mo7aNF2t8J3vQE2NkEopbNvA50siAp/4hF4s+b3vwYYNikgEslmbyy+HcePg5JMdzjpLsX59EB2N7d8YRpBnH/8hhbxebbxpvcHLT49izPhPY0gQpSDVl0OEokxlFxyy6QKh4Tt7jBj3+VSOAgEy3aUORK4nQxIfTzRvpQ+tYNSh3/j1wN7ox7QGXefj6LAfWaCmMoIvlqejK8f99z/Oc889TiYL554LdXVCb68CTET6MAw44wzd5n3rW9DS4uDzgWkWuOIKqKmBE05w+PjHHbZsiaHN0l9xVJTHHroE264DdvCrX1j8a9pkIhVnIuKjYCt2tOUwjNIWuqm0Q2dPASswvAgTb4UkNQYdiLEf23h1qOHiMUqpAlpirWEIyOchN6jz91QyydZCkhB6OLgS3YX4Bloj/DQ6PtFT6N5XAP0CRSflueyyHOm0w7XXwi23wLXX6jyvu05x552Kww4THMcglRJ+9jM44QR48kn44hf18V/5iv6/HzU1oMWuVcAvULaQTb8X3f/YChxLLj2VLevvLZ7jZG2cQdptuYw1DIwo99muFJmu0mIibMV9q1eTTvcSQ78sq9B9o0+h3TlPQ09sL0QPz33ontaoWRnO+2aeXE5x882aw1/9Sod0+fOfFX/7G8ydq4fK6bTB//0fnHgiLFoE3/gG3HqrfpluvlkXRQSqqgQ9Ob4G+BapvjS57KfRXYdtwH50dTSyed2/irfQ25Wjt3tgherpKu10NgyMLPfdKTJdpXj9Tt7mL8uWEC6ki8sQ16B18RPQzgYnuGkr0KvsA2h32tkHZTn97DyguP12zf3ll+v1TLffrvj732HiRM19Lmdw/vnwsY/BunXw/e/DbbfBhz5UqveGAfF4v5PuOuAsejrbKeS/75ZgG6ipdLRGadryUPEe+nqy9JXtWgm86u8hYuS4Lzh0NfeSaOouJSUyXPOfxxht55jsZroWPS9xDFpEfR/9C4D1cwijuT/kmBTHvTdHOAx33qnr8Xe+AxUVcNttut7X1DjuvvMm55wDp52mJdpLLtEj78MPh7/8RZfF54NwWNA+cBuB49i0cSu2/Wv027gFpRpYv17R0vR48R52tGZpaS3Jf0pBa3uOwtACbhSxx016Dw43HA5DJFzy1zZN2GHkmIu27P09q0+hG6dHgWXo9aYT0TGkUugewaz5+iWoq9MvCOj/GxuhtVXvobF9u0Oh4GCafsaPh9/9Dn70I7jpJliwAI46CjZtgvXr4dFH4bHHHHRTCboKJYGPo5cHXonuZ+TIZEuBy6y4HzNoDdzTO7b7vaQGcu8QG19DxeSG4r7S/niIJjvDbBSHUVox/C10Rbof7Y22gFIkVBv9XOYfoOeIJk3SfIMeKUQi0NmpveDa2x2UAp/Pz4wZ8Pvfw0UXwa9/DStXau5XrYING+D++2HxYhut2gOcglI5dFCMjWjuBZRFNtfp3h/UjakkWhnD70qEpiVUN1SQSe8+h8HBdd4K+YmOrqJySkOx4gdrojSlEkxBOw5Uuuf+GN2rvRv9DJ5Hrxg6Gd1JSgIHH6FYuRLmzIEqPchl//3dgJ1JaG+Hnh5tMQOBAPvsoztS3/ymrvtbt8Ixx8CSJZr7u+4SNm1SaAEM4OMo5aDr/yo090GUipPNutwbQuP4OHWjoljuaM7yG9SNio4Qq0PDYO791VGqpo6h5oBpRe4jUxpo6upiLNow9ItoP0MbiTvQc0ZPUAq0GUVLskccpVi7FvbbD6LurR5xBHR06Ea7qQnSaeV6Lvk59FC4/nrdQb3wQv1sjjlGtz0bN8LNNwsdHQZ6hlaAT+io2HwMvbL+Z0Acx26gkNfc+3zCvvPi7LNXrLgrYixmMmtqhPAwd/p8KwzGdvS8Wj/Gumk7PUZELHSd3mkgMKXU9Uqp/ZVS+8cwyeX1uovyDZTGGwEWoelZ6573JCX3zQ6gv/n9C3rdRTvw8vMwebI2DmvdE5cuhW3b9IM76yxobg4iMotAIMg3vwkTJsDee8Opp8Kzz8LDD+ue2bnnClddZZDN1kNx+dRtaOfR36OnebeiZ1SW4SsLbue4myeV7+mt3tgIYwS5N8h0dJFq6Sh6c+USaSaGQixGj962uef9Cz25GkVLg/3c34rm3vFZPPecxYwZusHZ5p743HPaUKxfD5/6FHR0hBDZF9OEb39byx/776/nj55/XnOvFHz968I115hksxMpRay+He3l/ht0eIQOdJSql7Asv3t/kEokcZxM0dXTLiiy6RShyLD5f8u4H1znC+kcid4kPa3dxYqf6U4yJl7JKrQI1O9hfzu6ztdRCgOi0NyPByqCPv73iMWsWbqut7n9locf1v8vXgyf+xz09oYROYJCIcf3vgdjxuie7ZFHwksvwUMPabn2618X/vQng2x2L7R6r9D1vgI9TXAEuou2N/A0lqk9DpWj6O3MkExkKbh7ehdyDsneNzTpPWLc57qT9HT20LNhR5H7VFMnYxsb2IDuFPW7ItyKlv/Go7nvD3t3C7rDVBEJ8sADJtOmwQsvlJYG/OMfuqP0+ONasUgmw4gcRy6X4TvfgdGj4dhjYf58eOUVzX1HB3zta8Kdd5pks4ei3XkcSjNVF6NnUhSa+ycQV+PO5xVbmjJsac4WvakSCZvWrhy5V61ye228Fd2ql4BpIjIJ/ZA+gXYYKMd96EHAc2jT+OhQgw/ubC5yXyPMVCPKc04fe6Ob6F60ve3BIIHDRPT4sxMo+KCmQmhpV1xwAeRyFl/7WoFoFJJJoaICrrpK4fNBImFQKLyA338Yra1dzJihr7ljh35wsZju+TY2Ks44A1KpJLrK1KIf1s1or+zPoOflAPbDdr5bLL+T126T5RgsUQ0RI8p9IqvIZ8p9muHQUZP4d2AlTdleZqAbqhS6p7UdPZ4ai347e4GcHxpHmaxZk+OySyGXC/K5z2WIRHQDVFEhXHGF1sn7+iIUCs/i802ltXUbo93AO01N+oWrq4Mbb4RYTHHqqQ766Y5G+2MF0VOQH0dPu1/qFno6duF3xVtIJXJk+gaO5tKJHAbDNhgjyn3Whny555yt+PDsvXho2XLaCmkmoLnPoo31evRobhRaCkkJZPwwqtFkwctZFr4CuVyIs85KEwzqLQIqKoQf/UhRXQ3d3Q3Y9mP4/dW0tvYSjer2cutWPZIeO1ZLU4ahOOUUGx21rRHdTahFSyTnoKfYv+YWehS2/c/iLaSTWkcvRzo5PGcDFyPHvaPo7DPIlXlvqXSeDxx2PI8+8xLdKs8Y9OS2nn3Qioag2fADWYG0D0bXw+OP2xiGYNtBTjstjd+vua+sFK68UtHYCG1tM3GcBzDNMJ2deerqNPdbtmhjPXWqdshJpRSnnVYAlrpXC6B1lEvRq81+D5zuljqGXXileA/NbbYO5FqG7e0Oodq3eQ7D1Qe/ht51cyXwN6XUchG5TET617PcCNSIyDr02/wqN7hdIRzWn3JJKhQSvls9ihkEmYYeJjYCHwxWcyVTOZcxHDbqCGLHfJdJY6v41Kfg9r8r/nYX1NeZ+P0FfvQjrdd+/ONw112Ku++G+npwZztIpa7iiivC3Hgj/Pzn8N//6uvffLN+eSwLxo0NcsCHvkgwWI+2+P3LBGejVyT0YzyaJg1f3I8ZGihJWbHhrzQeUe4NA9/h0wgcOR3cjaGs+jjG/hO56MSPMgY/c9BuKjHL4tQpc7mKaXyJMZwxa3/O/dwZ1E+q5uvnws03Z/nLXxShkOD3Z/nxjzX3n/+88Pe/aw1d78HuBwKk01dx0UUhbrpJa+0vvaR7ZDfcoI1GMAg1tUGO/ehn8Pnj6Kd/pnt7M9AvUT/GIaKNnhgwflIldQ0xQm6wQctnMHp8HFUYdvDBEePeiPgxKywC4yuK8cZ8dVEMs8Cl+xxKJRb7udybpsmZo2fwK6ZyDqP4xNyDOeP88wnURbjwQrjppgy33qowDCEYzHDFFZDLCd/6Ftx5p+KOO/pH8GHAJJ//Kd/4RphbboGLL9Yjwro6uOYarbtHoxCJBjjmQ+dgWhbaifQkdL2fgBsw1sUExNDcG6YwakIFdWNi+NyJVl/ApG5MjOFiRLmvqSBYVU1w9tQS91PGEjNCXHrIR/FjcJDLfdY0+diMQ/g1U/kUYzjx0A9w2he/gYr7ueIn8Kc/ZbjxRt34R6NZLr5YG4vLLtPc33ILdHWBbccBC6V+yJe/HOa22/Q8R2enlnB/+UvtLVpZqZ/38R/4osvr3sB70XP7DQwcdE3CNHUnyO83mDszypwZUfyud2AsbjFlXBhf/u0fYaCU+g86lFB52sVl3zOUIi4PC9lsfx76f9t2J8KzwjcZx+P00ESOU6qCbBh7JtdZjUghzebkKqR9A109fczuhQcegOOPhxkzbbI5uO8+vUjn+ON1vsGg1gpvvTWFbf8Qx/k0mcwXuP32G1HqQ8A/CQbT3HQTfPSj8OKLwo5mk+lTZjNj7gSWL/4xhfz96E7N02gXxf3Rg9MvY/lKLlCFZAHDbw2QpOxUYeB+G0PEiHHvOCS3JLDbeyGvK16hrZd0V4H8ug6+z3geo4cm0+HMjx3Hku5DuD6Ww7Yz9OQWkWzrYNOWLnbs0PLHscfCxEmK3l498ZfLlbiPRuGww+Dee1sR+SVKnUgyeSq33vovlDoeuJdCIcedd+p8/vc/IZ0JI8xm1twLWL74R9j2I+gVCH9DB2OYjVaUz8M0tYeUcqC5KY0tJumUNuCFvEPrjixjJg0/PMVIce8kc4iYFLqzxf218x1JfNEIVleOHzKRR+mh2VKce/LhTHhkMzZJphLmmeZW2jeupaMjxYYN2qvwyCOhoUGPJH73Ox2p9Bh3VV9VlZY+nnhiDfBHlHovvb3HcfPNz6PUkcC9ZLMF7rsPDjoI7rvPIBKvQ9nTmTn3AlYuuQLHsdCBSX6Ddj0Zhx7vfBfTmKjvyVZ0tiSJxAPkXfk1n7Xp7UxT+wbmMUaM+44e0tle8lu2lbjf1kLan8Pf1MqPmMRjdLMj5OPbp7yHf24+lDXBBEk7hdO3hIlbF2PbNkuX6rbrkEMgHlfMm6f49a91x/egg/S1Ghpg+nRYtOgZ4E4c5xN0dDzMTTdtwHH2A/5FKmXzv//p+ae//MVk+oyp5PKTmTnnXFYu+zkoEz26uxhtQ29Dz+9fgmHqC+VyDlu3pDFNIed6ByZ6C3S2Zxk9ZniumXt8aBDb4VXBpGxbf0yEY93pv9FBWGxF6DN9rF51A5nMGAxJUFmZx7J0o/W//8Hq1drgNDcbBIMGTz5pc+aZilwOnnhCcJwCOsjIL/H7DWzbwbYfAgJks9O4774e7rtvK6NGVbP/hy6kp8OPYWSZOfebbF5/F+nMlSjbwbbfh56QTQNHks8+Xiy/sp0Bq8H70/Y05HoKqJ4yyUBBtseh0JvDj8H7qAIbwuPn8MwOk17TZNXKP5LLzmbthu3U1urJvH/+U3uaLVumXxjb9mFZNk8+6fCRj+iFY88+KxhGAd3wXEwgYJDP2yj1KBAgk9mbv/ylidtvbyIQqOZz3/gZC56xMa0gM+d+i80b76aQv5RcTnDs49C+cgXgMLLZBcVbSCVz9CUG6ubJvhyZ7BtbODlScNI2Tnk4fUfh5BV2KkcQgw9SBY5QM3kaHcm19FLg+7TR13E0xgPLGT1akc9rGemZZ/S8UWsr2HYAvz/HM88ojjwSEgntiWaaeWz7GyilCAYNslkHPVPlJ5s9iBtuWMf117cSDNXzya9fyYuP9+H3VzBj7gVs3XgP+cL3yWVAqfejfeUEOIZstuTpms3YWP6BPGff4ILVkYTdKziJMu6zeex0EJXIEsXkI9SABKlsnMQda4QsBVat/AO2fQzLV69i7FibfF47DjzzjB5FLFgAuVwAx8nyyiuwzz56XmL1avD58jjO54vcZzIOWnXzk8sdxK9+tRSlOolEx/Ljn/+IP17fTjDUwMw532D7ln/g2BeQTNmgDkO7+fiB95LNbCveQjJZwDAHyoHJ5PDnTfc4L6nBiIS1HNEvSVmWHp5FyzolwYD2BPhocAWpviUU8hks82lEFnDttXDOOVpWam7W5517Lihlkk7fxq23GpxxhsGpp8KmTUJVlYXPl+QnP0ny3/8mePjhJNOnd6KHjAtIpzeRTjexeXOS9kQljXtpXyGfL8bMA7/IIaf+irpxB6DV5GVodfljmL5SmGIrHsAIWkj/Pt4CVqwshvueAMMgMnU8oTmTwaf7FWZ9FaH6akJ7TysN12dMIGiafGS+TVfH8yjHwuf7HyLLuO46zf0vfwnLl+tJ7NNP1xJIOn0j11xjcNZZmvv2dqGiwkcg0Me11yZ58MEEDz2UYvTodrRa/zzp9DYymXX0JlI0jh3N5BlxAPyBKo4/4ducd9ktjBo7B72efCXaJeI9BNyAZIYhjJ9SQePoCKGIvief32DspDi+QS/T7oRRGaUwbQqy7ywd3x2wxteTqR+Nb7+ZpYWU86fRY8Vw9pnJQ/SQ8jUgvgfx+TZw3XXw+c/Db34DTz+tRxFHHQWplEk2ezVXXCGcfbbBaadBX59BRUWAQKCPW25J8sADCR58MEllZQvIbOAp0ukdZDIvkkw61DWMYsK0CgCCwXo+dNr/8bVLbqW6bhI64M4a9EqoeQRCmnvTFEZPqqBhbMlDzR80aRg7fElqJCENNciE0ZgHzC3u0mbMmoxEw5gH7FU8ztx/L0wDPny0jx1Nj2JZlfj99xKNNvGHP5S4f+ghOO44mDEDUqko+fyP+d73hE9+0uCss6BQECKRAKFQkrvv1tzff3+SUGg7elXZY6TT7WQyD5LNmvjDcebN1/U+HBnDV86/lOtvuZmKikb0DuLrgBWITCQU1jJ3IGAwe26UWbOjBIP6nioqLCZMCuGo4XVU93iDkc64+3q7o4xCwd3T2w08mMLm2mwz52zfwD/yyzj04GYike3ccEMevx9qa/VxpgljxphUVOgHqHXtU8hmW2lu/iO9vfuTzzu0t+9PNgv77qvPE4ExYwTLqqTk/1OP4wTJp5O0ryk5XhT68iilqKk5BNO8GT08vxLD/Ayjxx5TPM7uy+mQITnXwiuwk2/IH33k4Dj0dPbQt72V/gBNdlsXvY5DcmMTOIoENr9f8zzn3fArnlp5B/vuvYPq6q389rd5Kiu15g24z8GgpgY+8IH+eF2fIpvdzvbt15FMzsC2HTo6DqFQMJg+XZ9nmtDQIBhGHaWqOh7l5Ck4ObZvKa1TaN2eIBqB6ppDMYyfoyXrH2H5zqe+8Qj3lhRdLX1kU5liGIt8ziHRkSQ6/MggIwanu49UR5L0umb64zsUtrWRKgjp1dtAKTrJ85tFT/B/f/gtf1r4KMvJMnrMZn72szyjRulOFej5v4oKoa4OTjoJTLMC+ArZ7Ca2bfsD6fRoHMehre0wfD6Lca4M7vfrRX1CI6UYU1Mo5BM4qkDTltL6nJZtvYT8DnUNh2MY30Vr6v+Hz3c5tXWHAXqxbU9bglRPquihlsvYpHpSRPecMF6olg7yPZ0UVq4tBrFz1m4mJzkKK9YA0EKOXz/3L8674Q80b7+L+rptTJ26hYsvzjN+fH+4D13/AwE9N3raaWAYDcAPyOXWsnXr78lkKnEc6Og4nFjMR3W1Pi8c1s41pe2WAKaQyfQhAqtXae6V0t+TfQXqG49EjC+ipfBv4ff/gcqqQwHIZh3Wr02xfl3SHb1AT0+Bpu2ZnW4X8VrY4w2GcopSYilN6TSF4hq2M4oEN9l5Dlm4mv/8/TH23ddmwgTtQnvddXry6IknYPlyxebNeng4dWoQrfnlgBosaxXHHncA06Y14/cLV12lz3vxRXj2WYVltaA9rncAF+EPVOELVGDnyoZ1bkED/mpmzj2f+sZV1DY+ypyjv0JFZal3ohz1qptSg29yD0B1uptYJlFKUFCf6SSUTmKjuIqt7KUS3NrRzrRHF/D8/xZw1FF5pk3TDdZtt2kOH3gAtm/XfvwbN0JDg4OeZwAI4/M18Z5jD2DatI0YhsM11wx8ZmKsQDvv7gDOJRyZSTwsOGXBcgp5h1A4hz/QwIw551LXuIhxk57ls+ddSDQ2rXQLqoBpDPLMkTzhyBvy1hkxBHrasJKlWFI4inBvK0YqRQ6Hn7GVoxzN/YxcF50ked/78sycqWWme+/VHN51F/T2Ck8+qd064/EeSgHnbYLBJMcccwBTp64llyvw5z/r8/7zH9i2TWGYT6EDbjYj8jViFXsRitjY5dwXbEyrQCg0kWmzv0xdw7NMnLaQM798md4Ho/8W7ALKGdgxUk4On3/P4r4qlyaQLZMtCzZ1ThYrkyOJzU/Zygn5Xm7p7CTz98fo3raND30ox9y5sHmzdpDp7IQ//1lQSrj/fj1YCYU2ouNORIEOIhGTI4/aj8mTV9HVleOee/qfmdDTA5b1D3QA9W2InEdl1Rz8pu7k9COXVTiOEI3PYtrMz1Jb/xiz567ha9+4gkCwFN4kn1ev8jgt5BWmMTwTsMcbjEhEb4jef1+WpSeoY1FIYLORLH9Ch+f6gaOYoRRLl5qk09obYelSvUL4F7+AfeZNIxDQ3jY7diSJRvVKAV/wq/h8adrbXmbSpK2IKBYs0OddeilMmGDyzS8fw+SJP8S0ZhKN3c93vvV1nr5WFSUp0FKTiOCrCOAP1DBm/EeYsu8ZVDbOwiyLFeWr0JKU0S9JGeCL71mSlBgGEyb7mTA7juF6tURGxRhXlWfs3jW0GHky5PkNOk7DTwo21QWb554zsG248kp47DHN4TXXwIypk4hE9KRrMpkiHP4tMIm6+oswjCS9PQuZOHE7IqXzfv5zaGy0OOPsE6lv+AamOZNYxYuc981zaaz3s/8BlUWpct99KxhT4Wfv+RUEQw2Mn/hRPv3Zz3PMYfOY4MbMsSzhkAMr2X+vOFVV+nmEQgaH7FfJ6PjuXzjZj0BFgMn1ecZPCxb3kY+NjTHB6mTMrDgbyVKFw4/R3F8DGCiefEz3bn/2M7j7bjjzTL3gdHR9PfG4fgdsO0UodBkwkYbGq3CcHtLplxk/fjtKwb/+pWXDP/wBqqp8fO6cE6mq/hymOZuKqo18/ZtfZky1yd776uGjCMybX0F9lcnk6VHC4bGMn3Qip33qHPY/cAa19bpe+/wGc+fFmTUnRjiq61M4YjJzdox4eM9phqzRtfgnNhI+eLYe4gLBvadgRkKED5nDKjLMwuF7aO7/lM3T05flySeFWEzX+5tu0tzffTdEoxVUVOh000wTCFyA5v5m8vkOlPMKY8c2Azqu1Omnwy23KIIhi4994gQi0dMwjHlUVic44eRPAbD3/BL38/epoKLCx6TJYSLRSUyaejKf/eI57Lv/ZKqrdZ0OhgzmzI0xe06UUEhzXVXlY/KU4Q+r95wntQukUpBMURaWFzJZ6EvqSe88iv4tfhwgZRrMmTOTM87QBqO5GX7yE/D7/Xzi9OMIh6GvD6ZMAdNMYphZxkxoZP58xS9/6fDtbztccgnk88I//qGHh5GIyfQZ41i34iry+X/S3f1rLr1sPhgmrStLm5QUElmUUuTLwh0UElk9Cd5XMu+F3pwOD9I/OnGgkNizJCnlOHSt7KZ9cVsxbEmyOUFye4a2RS1Yjg5f3l9qG0hm8vh3WJx+OlxxBfT26kbfcUzOOONYAgE9fzFpEvj9SSIRm3FjwxxzDPzkJzbf/a7DBReAUgZ33qlfiGjUYt99prJs2fXkC/+kq/MXXH7pNGJ+xdIlvcUh9bKlvQQsxfKlekTkODotm8qzeVMa0CGdVy1P0LwtRVeXfh7ptMOGtX0E9xx7QbYnS/e6LjqWtRfD4ye2JUi1JGlf1oaF0IcqrhzJAnmE5CaLM07XBiOf7zcQJp847T3FvCdMgFCoj4ZGH/F4npNPFi67zOGiixzOOQcsy+DWW/V7FgyaHHLwvqxa8yfyhXtpb7uCS34wkZqowarlmmelYM3KBAawaZ2WShwH1q/qpa87R7sbjiKfc9i8vo8dW1Ok+nTJU0mblm0p/L49Z/6o0NROflsb6QWr6d9lK7N0I046S3rBKnxoH6R+PSAJKENoa6vh7LP1fJ3fr9ucUCjE+99/KNmsThs7FuLxPqZOrcQ0u/jMZ4SLLrK59FKHU08VYjGDG27Ql1UOzNnrII45/lL23v9yJk45jVWrdATdZUv1yFMpWLq0l0SiwKaNuhUsFBTLlvaydWuazk5dxzNph1Ur+1izOkk6retTV1eeLZtLm6MNFW/KYIjIz0VklYgsEZF/iEjlLo7bJCJLRWSRiCzY2TG7gir+MyhRQQSTw4hxPML1wBl+i8Ck0fzngauYPHkC27frSe5f/MLgiCPm86mzj6ciVsesWQaTJ0NNjZ9TTj+JXCbB1KmlYd7EiXoIFwppHbKlNcyJHzqQfi3XMMSdeJRdSElqp19f+z6HJ0m9LdwrxeC1To7S8lkdPqYS4oMu9ycg1BLkwvw4AkkfO3ZoWeqKKwxOP/1YPvXJ92NQyZw5BlOnQjTq5/xvfIpEYiD3EyboSl9RoY21bVdy0CH7FkcS/Qu/RF69T0p/mcvTBmu0Sg08r/zcoeLt4N5XV4MRGSju+0c3In4/kwgQJ8BJLvcfQJhDmIty47F7TdratHZ+6aUm5513Eud85sPkshHmzoVp03TolW9ecA7pVJLJk0s3P2mSNjR1dXpE39Awlnl7Ty+O7g1DB+gM+AZKqqIgFlIDeDQNRcg/kGi/qQhYA8kOWIqK8NAfwNvBPY5CvWoTHp02ixApfJzRz304yGc+9T6efuZ60ukwXV26bl5+ucm3v3MWXzzn4/T1BZkzR7vQKuXnS1//MrlsmkmTSvc9ebIikxHGjNG7ifoCU2loGDOgrjou5+VNjuov26C0we2SrveD3uU34Jj5ZkcYDwNzlVLz0K4R33+NY49RSs1XSu0/nAuEQ7rhKJekAgFtCETgkzQyz6rl3+EYDfNn8+BTv8UQIZvJcNRRwje+AfPmQWtrF2EzzzP/uYzDD/kYsdgxfP8H51Mz9XQCNQdy773C2rVa/736aoPaWpOHH4b2dh9PPf5b4iGBbJ82/UpBLgNOgYY5ZZJUTEtSVrzcI8qPmAZm1F2YJ6VYUv1SD4bgG/7CvRHlXgyDqjkTqZk/pbg+JDyqiujYBur2nYJhmnyJMUxpmMzDs2cxbupszmUMDgJBg/e/TwcNnDFD2LGjncpgkBceupZ5e59ENPYefvqz73HCSR9n/4MO4o47hM2bobsb/vAHg8ZGPborFILc/8A1ZHM+WtsK2LY2YB2dDrk8zN8vjmHoerDPPnFEhH320R4khgH77hunstLH5MlakvL5hL33jjFlSqg4XA+HTebMGfY6gBHlPlAdJjalktp9R2G4iybjk6sJVPup238MpmFwHmOpHzuZR+ZN5eD3Hs55o2cTmFCDEbI44QQ47zyYOFFobu5gVDTOM3f/hlkzT6Si4jj+cO0Pec/xx7PfPntz881CU5OOWXT99cL48YrbboPKyhj33/cbghi0tuVxHM19S0sB04TPfLaRhgYfo0f5+ORZ9UT9wmyXR9OEfedXMG5UkNGj9bsQCBjMnxdnzswo8bh7T3GTOTOjDHNwN6Lc+8bU4p/QQPig2UUPteC8yRjhIOEDZ+MzTL7NBGTSbP49ZxYnfOssfnPdBSSTWVAOH/+49sIcPdpg27ZWquKj+NP1VzNh4keoqTmem2+5ghlzD2X8xFn88Y8GbW06isTNNwszZ9pce62WsY58z7eIxnzsvXe82PbNm1cx4H/DgHl7VxCL+5g8WctLliXsNa+C8RNCVNeUZNdZs2PMmhUjFNb3VFXlY+Kktzm8uVLqobI/n0cvwX9L0e8NVS5J9XtJKaX3lT66UMWYeph/zbnE4hGef345tpPgq1/VW3DuvbfDmWduZf32BNMaYvz4yq8UXRPHPpXCZ51IYn075577IIWCwu83yeUK3HffaB597FImTR0PvW3gC+rlwgD+IBgWO5a3FstaSGRR9WEKPaUJs0JvDl88UNyyFQX53ixiGKUItY4in8gRqBn64xhp7pXj0LViO5mOBLa7RiHV3EWyqZO2VzaibAcL4ehWk30//WFW3PgoGfIsp4/6hjyf/ZzOZ+5cm5NOWkJ3JkPDqGp++cuvF6+xvcnmwos+T7qvmS9+8WlsGwIBzf0zz0zgmWd/xORJNfT2ZamvszBd19eaagO/DxYt6CnWi4ULeznmmBoWLtTDdceBl1/uYezYEBs2aEkqn1csWtRLKhUtDtdTKZtlyxIcdFDV0LkZYe6znSn6WvN0rejEcRdN9m7oJO8EaFvcgnIUfgyObTE56LsnMP5z78EM+bn11oeY+6elnOEGyZg1q8CJJz7B9b/5NhMmj+JXvzm/eI2t23Nc/btvc/anO/nMZxahFPj9PvL5PJHINJ559kdU10fo6sxRXW8VR3YNDRbr12f42AlxzjpNN1x9ScUDD6ZZsVxLUrYNr7zSQzRq0tSk34Vs1mHx4l5qa/309rr31GuzcmUf8+bFh8zNSHOf395ObtMOUs+vKHqoZZasx0llSL2wAhxFCOGjHT7GfeaDHPyD4zBMg3/96xkOP8Lm5JN1PuPH5/nCFx7kwu9/nXmBCZx46gXFayxeafP76y7ja188nzPPXIMIGIZFU1OBqupJjJ9yDps2ZulLFFi8uFTHFy/u4chjqlm8uBvQdXzxoh4mTAizYYP2GCwUFEsW95DLxejsKMmuK5b3YhhCOqXvqasrz8YNKaZMHV5n6a1cuPdZ4M5d/KaAh0REAdcppa7fxXGIyBfQ0ZmpxULk1aqOqwYNSgSV0w2baZrkcnqYpheKQaHgYJmvHlDl8pArKG7803e58U863tPVt/VSM7WO0w8uX+Dl6mDFP/Xfxk7y1AVUxXKB6P/7k0ReVX6RwTc0LIwI94ZlIIPuT0wTwyzFnxG3i99/nIGQy1PkvlDQ303DcIfOqnivjqM/9/zj8mJ+S1dlGVNjUl1XqpraqezVUpNZvgGV+900SzH/LcvANHU5+k/XaQO5toYZsXMQ3jT3g3kHMMIhjIC//CCd5i/xYvhMzHi4WK9M06DcuSeXAxAMEWDQQlFH8PlMHn3s18W0fG8e2wfBkO6Zqn6pY1C1N3zmQKnE1vtG65hJ/dzLTniW4nMqT3sTGBHusUzEKoux1F/Hy9LEskApd29yzX0uV7qXXE7XReXsRNZ1FKbl58WXSkV6+LEcf7mjlSWLe4qX7M+3H/1cWaaeu+3/3i8Vlur4zrkX483X+9c9Q0QeEZFlO/mcUHbMhehltbfvIpvDlVL7okOwfFVEjtzV9QZHjwyFtSzVf6/9klSkbII/GNTEtdz1HMpx2Gf+VEY3juYnV/h4+GG49NIABx+8FxNHRbWklNMLO2xH+O/TKVauy0NBjwASfQ6PvZBmyVZTbxwOYOchn4FskuLenoUsODZ1M2uL5ShKUmXykhXzI6Zghn0D0oyAWeYlJSXJag/hPm74iE9rpHrOuGIjFR5VSag+Ts288cXKVzVzNKbfonbeBBCYSYh8IsxVV1k8/DD83/8FOOWUI4n5/eDoMAWg/fJb22y6ehzybgTNbE7R0m7T12cXG56+pE2iT9HRYRdlka4uh3wB9pofK85tzJsXQ0TYa6+Yy4tOi8d9TCzzkpo7N8qECaEBXlIzZrzaW+Tt5H5wnQ/WxYhPa6T2oClFSapiRiOB6ih1h5QWTdYdNh0RIbWpE6UUH/rQwTRvD3HN1VpOvfDCAF/96keQlA1ZB+WOVmxb0dFZIJko8WzbDk7eIZexi1p3LqPI5xTtbYUi921tNkpBc4tdnOPa1mTj8xnMmKl5NAzNfV2dn1GjtCTl9wuzZ8eYOjVMLKbvKRYzmTr11Yswdif31qgafGNqCe03A9zGOjhnIkYooNPc+hbaTy8W6tjUjVKKU045mkWvBLjhBoP//hcuuSTI+ed/gs4Om75eRdZd/5DJKZpaFVu2OWTdet/dXaCjUzFndqzY0E+YGCYctpg7t1THZ8/WI7HZc+MuBzBnbpxo1GLCRM2jaQmz58QZOzZEVb+XVNBg+owY06dHCbpeUpWVPsaOGwFJSil13Gv9LiKfRi8xPHZX0SCVUtvd/1tF5B9oj7Qnh1LApLs2q3++plDQi/lSZRP8mQzkC4pRZx+NGAaWYfDgQ7/lJz/8PatXt/O+983k2985EzHRDX3AJVcUJx4XIeBPgRsCOxY1+OBRYSonFiiGdzR94A8NlKR8QTAtdixtKZaj0OtKUmUhm/M9WS1JlUXlzPdkEUPKvKQUhd4sZu3Al2d3cq8ch67l28h0JHBy/ZJUN8ntnbS9vKE4qda5fBsTPpSj9eUNoMCPwYW5iTxdMYY1a3r4xOl7c/75H0cKCtIOAXfexjSFUY0mPQnwuTH6A35hdINFLF4aBUQjJpVxm/o6syiL1NSY+P2w8MWSl9SCBT0cc0wNr7xS8iBZsKCHMWOCbNxY8pJauLCX6dPtAV5SS5cmOOSQgZLU7uQ+05age9lWOpdsKUpSPauaSe/ooeXxlcWXoeXRFUw5c28iU2oRESoqojz92O+5/Id/ZM2aJF/+8oF86csnQqqAIo/4StzX11n4RRV5Nk0Dx28QsKTIcyBkEAgKNQ1mmSRlsmGzw9jRZnGkOGG8xbJluaIk5TiwYEEvoZBFc7N+F3I5LQfW1vpIJPQ9JRI2K1b0Md91E90TuC80d5Db2EzquWX076qVWbIBuy+t09yrpZ5dTs0RE6mbWo2I0NhYzSMP/55LL72F9ev7+MGFR/CpT32AjjaHRI9DwF1hHfQL40YZKFsRcOt9ZaVFQ73Dv//dUzTgGzek6O3N88orPcU6vmhxN0ceU8XiV3rce4RXXulm3Phw0UvKLigWvdJDJmPT1e8llXFYtrQXw9AeUwDd3Xk2rE8ybfrbKEmJyPvRYSqPUkrt1EdLRCKAoZRKuN/fC1w21GuYxqslKdMoTYL3wxAo9JRW/kbCAS7/wWlQORpM9zbzmZKe4Vb23j6HRHLgFXr7HPzZQUPlfv2kH24+vmAZhf3DIEPAffBiurOy5ZKUKaVjKUsbBt4O7q1wACs1MO6SGfRhhkqjIcOnJSor6KP/yIp4mG9/+SymHjwGwx32Ovn8qySpfF4b+nLk86o4sCumFVRRZgKwHX1Mf28JIBTSDVggYJByddpQyMDvN9zdzPRxwaBJKDQwpHMoNLyh+dvGfbjkPCGmgRn0YUXKHCoifj0XlrMxXMeE2sooP//OpwnNGVscBTrOq71mCgXFYEWiKEGV/e3YCrs8yrqtq36hgF77h35mliX4/VLcbyEUMggEBl4gFDJ2wv3wwmuPOPcCRiiAES4FoxSfpT9laUY4oFWKfIn7xvpazj/3qxx8REXRwNoFhT2EOp7LQShY4sI0BZ/PIFiWFgrqOh4MGvS5rsmhoInfryWofmMTDA48D/S7Yg5qc4bLPbx5L6mr0XG9H3bd164FEJHRItIfSbIBeFpEFgMvAvcrpR4c6gWCQR0rqjy8ud9fCn0AWqIyTaHjgYVFNzOybl3KpUpGol9Syusep+3AkwsyrN+SL2680ZdyeG5RhpXN5ZJUQUtWufSrJKnqKdXFcpgRn5akyuQlM+JDjEGSVMSP4TcHxJIyI8NeCDCi3IthEJtQR8X00UVZJFRfQbA6RtXMMUWDF5/SgOEzqZw5pnhuzQETAEh36WeglEKl864k5UogjpaZehNOceVqLq/o6LJJJktSSTJpk0orOrtKUklvj0PBhpmzS1LSTFcO6f9fBGbNihKLWYwdW4pnNHNmhFGjAlRW6pc8GDSYMmXYsSlGlPtATZTIxFqq95lQ1M1jk+vwV4ap3ndiURap3n8SAOnt3UV5KNfcrd1C+4P6KYXTl4ecU1zTYduKrm6HdMrGKZOkVF6Ry5VJUlkdwLCz0y7q8B2d+p1obXeK12xpcbAsg0kuj4ahn0N1tY/6ev0u+HzC9OkRJkwIEYm4C0EjJhMmDFsWGVHurfpqrPoqAntNKvZK/dPHYgR8BOeWtiwI7qW/d27pH9EqOprSZLOKZJ8bUsRRdHc6JJOKXJkk1dKu2L7DIeeGFu/ptenuUUybHi12hMeMDRIKmUyfXqrjU6fp7+WjgukzooTDFmPG9Ndx/XtDQ4CKSt2mBAIGkyZFmDgpXDTiFRUWjaOGv1j4zXpJTd1FehPwQff7BnTg9jeEZAoo86fXez4PlKSyWW21G888qjR5HIxBqhuC0ZK1Ccb0KMPvSlIGfPQ9YXyWgKXJjYYNPnBkmMoJ5ZKUtQtJykfLspKXlJ3IoRoU+QFeUjuRpHq1JFUeS6rQm8OsHZaX1Ihyr72ktpFu7y3KIunWHvq2ddD28oaiLNK9qolCOkf7wo3Fc1v+t5rGbwmROl2xRQQj4oeUU6ywpiGMHW3S0atXAQP4fcKoeovKCrMolUQiJhWDJKmqKpNAABYuKIXOePnlXo49tpZFiwZKUmPHhtiyRS94sm3FwoU9zJgRpbtbN6iZjMOSJQkOO6xk+F+XmxHmPtvRR/eybXQt2YJyPXV617aQau6m5YlVxZFqy+OrmPrJfYlMri3W++CEOnKbOzD6OygiGBUBFLniqnHTFOpqTQKGKkYwLUpSvjJJKmgQDGlJqj//hnqLDRtzjBllFNPGjTNZtDjL6pV6hO842mstHLZobdVzg/0earW1/mKU1GRSe0nts89ASeq1MNLcF1o6yW1sJv38iuKwNLt8E3YiRer55cXjks8vp/aYydRP0VKmiNA4MUJ3JkPMdRs2DKG23qS3x8FfLkmN1pJU/4LFirhJQ73Dff8seURt2ZympyfPokU9xWsuWdzLMcfWsGRxqd4veqWH8RPCbNnidoJttJdU1qHH3bs+my15SWWzpVhSG9YnmT5jeMEfZRcS4B4BEWlDb+0Feluv9tc4/M1ipPMf6jUmKKXqRrgcr4t3GfdDzX+3cz+Id9hzuBnp/D3ud1/+Q+Z+jzYY5RCRBcNd9Lcn5f92XWMk8E7n/p3KO7zzufG4f3flv8fHkvLgwYMHD3sGPIPhwYMHDx6GhHeSwdjlCuV3SP5v1zVGAu907t+pvMM7nxuP+3dR/u+YOQwPHjx48LB78U4aYXjw4MGDh92IPdZgyAjFvReR94vIahFZJyLf28nvARG50/39BRGZOIwyjxORx0RkhYgsF5HzdnLM0SLS45Z3kYhcPNT83y543O8+eNzvPnjcDwH9qzX3tA96Ob/lfv8p8NNdHLcJqB1iniawHpgM+IHFwOxBx3wFuNb9/gngzmGUeRSwr/s9ho7XPzj/o4F/725+Pe73zI/Hvcf9nsz9HjvCUEo9pJTqj2LzPDD2Lcj2QGCdUmqDUioH/BU4YdAxJwB/dr/fBRwrMrTY40qpZqXUQvd7AlgJjHnts/Y8eNzvPnjc7z543L8+9liDMQifBR7YxW/9ce9fFh3b/rUwBtha9vc2Xk1u8Ri38vQANcMtsDus3Ad4YSc/HyIii0XkARGZM9y832Z43O8+eNzvPnjc7wRv5QZKw4aIPAI07uSnC5VS/3SPGUrc++0iUo8OSLZKKTWk0OkjBRGJAncD5yulegf9vBC9FL9PRD4I3AtMe5uL6HHvcf+Ww+N+9+Ht4n63Ggz19se93w6MK/t7rJu2s2O2iYgFVAAdr30nA8rsQz+425VS9+ykvL1l3/8jIr8XkVql1EjHsRpcDo97j/udHeNx73G/a7wVEyEj8QHeD6wA6l7jmAgQK/v+LPD+1zjeAjYAkyhNQM0ZdMxXGTgB9bdhlFmAW4Bfv8YxjZTWvxwIbOn/e0/5eNx73Hvce9zvNK/d/ZBe4ybXoXW9Re6nn9DRwH/c75PdB7AYWI4eVr5evh9EexKs7z8evbnKR93vQeDv7vVfBCYPo8yHo/XNJWXl/iDwJeBL7jFfc8u6GD2xduju5trjfs/5eNx73O/J3HsrvT148ODBw5DwTvGS8uDBgwcPuxmewfDgwYMHD0PCmzYY75awAO9EeNzvPnjc7z543O8+vBVutQXgAqXUQhGJAS+LyMNKqRWDjntKKfXh4WTsC8RUMKp3DlQKcBRiiPYL6E9TbpoL5e41PaQ0keJ234YhhINCNqfIF9SAa2KUjiuWwyzPC2CI5Si7JspNK8u/r3Njuxr6VpUjxn0kEle11boYtqP3w/ZZpXIWbIXjUNyXGCjy5rdsbCuAIZDPOYgBQXff7pwN2YyDGHpPaJ2fg+Po/BGDQgEcR+HYDqZlFPeYtgv6OMun8xKBQl5f07RKfZ9CwUFE71OtoSjkHQxTMAydppTCLjgYZin/lu1rdjv3wVBcVVU1FLeOt+3/x95/h9l5lPf/+GueevrZXqVVb1a1LFvuvVPsgAk1lBRqqPkESGihptACgRAIoYRAqAFjU1xwr7J631XZ3ndP70+Z3x9zds+uMSDZFtL3d+m+rr12z+ycmXneM8/cM3eV6pkNbRZ7z5WAj2YYCCQ+Gp7r13AQgFT4GYZAxwOhI4XK6Sy0OTj4EtfzMU3BzPnR9318T1axV/mqHcdHSolh6BiGeg8q5Tl9zoDieAhNzGL/TDjPlOlGLS/4mYB9MBiTDY2ts2PyPB/fB8MUiOqm47o+EtRaVUDjOBKhgaFroIGQEsdR2BvVfcKXqDJTw1Qpv9E0MDRXrWupcrC7nsT1JAFbn53vcsVHSrCtGs7lilrjllnDuVyR6Lqojk29QxVHzhuH56n9zZqTu/1479ETxv45Mwwp5SgwWv07K4SYcU1/+uSdNJlmAxuu/hgAxcEMSBCGRmhhDK/kUhrNAaAFdIILYjjJEpVplQzdiFoE2iKUxnO4GZWI3moMYtYHKA5l8UsqAkCgLUJ9m81/fryJ9haDYsnnnZ9McKi7RGEwM8scgl1x/LJLaaTap13tM1OmMlkAQA+bBDuilCfyOOmyeob6AFZjkNJwFq+o+rRbwxhhi8JgGun4ICDYGUUPmjz83VfOzSn8e+lUYi+0et7+pn8kX/C48/4kng91MZ2XXt/AscEyDzypTLsXtFm84Mo6tu3JseuQwmH9Sjj3mmU8dNcYfcfzANxwQzMbNsb4+jcGSU5VEBpsvGQh9fUWj93dR7nkYVka175kCRMTLjsfHMD3JMGwyYXXL2JqLM++x0cBqGsKsvmKDga6Uxzdr8zVO5bEOee8dvY9Mcz4UBaAFRtaWLi8nu3395NJlhACNly0gHhDgCd/00e56KIbGudftYhI3ObT773mtGOvafUsWfH/uPzKTlKpMk89OY6UEK+zuPTyDnqPZzi4PwFA24IIWy6sZ9eODMO9aQCWrGlkydpGdj04SHKyiBBw0UUhOhY2cNevxslmHDRdcN7lXRiWzlP39eE6PlZA5/yrF1HIOux+ZBApIRK32XrtQsYHMux/agKApo4IV928kF2PjnH0UBKARasaWLG+hZ0PD5IYV/N9zpY2WhbE2PabPgrZCpomOPeyhQRCBtt+049T8TAtnQuuWUQwbJ0R2AutnmWr38v1N3QyPJTnyScmAWhpCXDl1e3s35fk4IEUAMuWx9hyfhOPPjLO0KB65nM3N7J8bYz7fjnM9HQFTYMbb2ylucniRz8eoVDwsCzBq17RwYrlNtdeE8AwBIVshXt+WWDPgTw/vzuFlLCgw+L1r2zl0Scz3P+Imtv154R5wfWN3PHrKQ4cVu/alZfWccHmKP/zw3FGxioIAbe+oImFnTbf+t4YmayHaQpe87JWNA2+84NxKo4kGtF5/avaCId0Xv6qF50w9s+rDuP5cE0XQrxRCLFdCLHddXJ4eQcv5yjDMUC6Pl7Jxc1WZr/jlzyk4+PmamVutoKUcl49N1tBuv4sswBwcmXWrrBob1G8MxjQuGSzjZuvqGMBID2JV3Tmte+XPXzHm9e+l3eQvsSZ22euUv1+rU83W8Eru4pZAEhwc87vguSE6PnGvlLJMTRW5vhQGa86zFTGYyrpcqy/NPudobEKpYrkyJyyI/3qNDXDLAAOHswyNVkhOaWwkT5MDGWZHi9QLnkAVCo+owM5Jodz+J7Cvph3SCdKjA9kZ9tKTRUpF11G+msOreMDGaSUs8wCYHwwQyFbIZNUY5MSJoYzJKcKlKvz4bk+U9WDx7Ol54r9vDXv5iiVPKanS4wM55kxYkynKuRzDsNDtbGODeXwfcnYwBwcBrOUiy7JyeLsMw8MOExPlclm1BrzPcnkSI7psRxudQ1WSh6JiQITw9nZPnPpMrlMhZG+GqZTI+o7A8fn9pmhUnZnmcXMOLLJEoXqu+D7kolhNd9ORc23U/GYHi/8YYB/Dz3f2OeyDonpMgMDtWeZmChRKnn099ewH+jP4XlyllkADAzkyKQrTE/PPDMcP55neKREoTCzxiW9vUUWdBoY1ZtAKGrR2Kxz+GhpFvuhkQrpjMf+wzV8DnbnkVJysHt+WSrtMjJWfa8kdB8pMDRcJpOt4uxIjvYWOXq8SKV6I8/mPAaHyyeA8Hx63hjGCbqmbwT+DeWa/owkpfyalHKLlHKLYUTQAgZaQJ/TEWiWjhaoXY6EIRCGhmbXyrSAjhBiXj0toCN0DTHnCq0HDHoHXQolf7bs0DEHfU5bCNBtA31un7pAMzT0OWPTLF1dx+fU020DoQuEOb9PzdJhjrhq7ndOlk4F9qYZoanepLXRnP2/ZQriUZ2WplpZPKpjm4KWOfVaGsE0NRoardmyjo4AdfUmdrCGQ7whQKw+MHs1FgLqm4PEGgOzdXRDIxKziM8pC4QMLNugbk5ZrCGIEIJY/dyygKo7Z45i9UEi8Vqfqqz2nZOl5wP731rzmiAWt6ivt2fr2LZOMGjMK4vV2apuQ3DeM1u2TjBcW0+NDTrxuIk5Zw3GqtjPPocG0boA8YZamWnphMImdU21snDMxjA1Gprn9FkfVHUjtTUQawgQilqz4kOAeEOQWH1gVtQihHqGZ0unAnvTFMRiJo2NtXGFIwa2rc8ra2y00XVBXV1tjTc02IQjJoE5662lxaap0UKfI8JubbWYTnizn13HJ5PyaW+dg19UJxLW6Gyvtd/eZiOEoKNtznvVahOJ6EQjtT7bWy2am8xZhjRT1t5WG7+hi3nv8YnS8+KHUXVNvxO4S0r5uROo3wdskX/ANT1St0RufuE/AuBkK3iFCkbUxgipB3VSJbyKh1lno1sGUkoqiSL4EqshiNA1pOerMk2oMiHwKh5OqoRm6ljVl2b1EoObrgix62CFB7apE6mbq+Dmn9ZnuoRX9jDjNrpd7TNZAs+v9elLJRoTqDJN4DkeTrKEZmqYdQE1jpKLky6hB03MmJrMh7/7yh1Syi2nG/v2tqXyo+//NAA9vUXGpiqsWR6iud5ESsnewwUyeY/Na8OEgzquK9lxQJ2Azl9bpNy8FM2T7Ng2TTCqc/WlDWia4MBAib3b0sTqQjQtrMMyIDWdZWo0x6IlNo2dTUxO+UwMpklOFOhYUkd9cwApJf3dKQrZCotWNRAIa+gCevYl8T3J0nMaMUwdp+Jx/NAUpqmzeHUjmibIZ8sMHkkSidssWFYPQHKqwFh/msa2MC2dMQA+/d5rTjv29Q1L5Kv//LM0NqoNua83QyZdYenyGJGIhe9Ljh5J4bkVula3E7Ir5JwAxw9No+uCJasbEYbAKZYZPJKiqclk+cIKwoyTKgoO7EkSrg/R0VUHwORojonRLAuXRojEI2hCMNybIpss0bmsnniDiSGge3+CSsllyTnNtLYYOCWfXU9NIgQsWdOErmuUiy69h6cIhk26VjQghCCTKjF8PEm8IUTH4jgA02M5JoaztHRGaWyLnDHYNzQukW98279S32AjpaSnO00u57J6TZxw2MTzfA7uT+H5krXr6jFNjXLZ48D+JIGAzuo1dehBgZOtsP9AhtZWi7VrogCMjBQ5cjTPwsVB1q8KA7BggaCzscjwsTTjyTp8Kdm1P8/kdIXLLq6nLm7ieZIHnsjglHwu3honYGuUSj6PbksTsDUu3BJD1wXJlMO2nVmaG002b1R9Do2U2X8ox+KFAVavVH12Hy3Q219k7eowCzvV3vfyV73ohLF/zjoMoTRE/wUc+l0TJ4RoA8allFIIcQHqZvMHY6VI18d3qle5yTzSk/glD31hDL/sUp4qKMWx6xNoj+BmKziJ0kyn2E0hKskSTkpdvTRDx4hZVKYLSswllC4iXGfy7jfEWb3U4vLzAxzpdxgcqlCeLFRFWB76gii+46s+fZCOT6Ajgpur4FT1JkiwW8I4qRKJ/t2MDD2E1FzaV55PQ/ziWp+Wjh40KU8W8Esubs5Bs/X5t5rTjH2u4FEs+RRKHo/uzFKuSBJpjxddVc/QWIVte3N4vrruXn1RnEPHiuw6qK7nAUuwshmeemKaA3vTaBp0NlusWhVh24NTjA4UMcwc54Zt4nUW+7ZNkEs7jPTrXHNrnHzWpXv3BE7ZI5sqc/7VC0lNFTm6fxLfkzgVj3UXtjLcm6HvsHoU3RAsW9tM76Ep9m97kLGRx7CDOhdceR1+ZS1TY3l1W4nbROI23bvGyaXLTI3midYFCYZP7rR1qrAvl3327Znmkss6yGYqHDyQwHMlxaLLBRe2MjKcp+ewknM7cpr1m6L09yQY6FF6DTto0Lmsjp4904wNZhk4KoiYIZrbfbY9NMXURAnTzhOvC2KYGt27xigVXDJTBTZfEaRccDmydwLX8SnkKmy+opOx0TzHD0whpZLStra0c/RQgv5u1adlG3StaODo/gkO7PgNE2PbCUYsLr72heRTi0lNFRkfzBKts7GDBod3jVPMOyQmCpx/VQDrJG/Xpwr7Uslnx44prrq6nYnxEnv3JJXiuOJz0cUtHD+W5eDBFKBu0GvX1XNgf5IjPRmEgEjEZOHyME8+Oc3QUJHjxwRNDSZ1dRYPPTxNMunQP1BgUYdNR7vJli02wUCQhuYgU/eU6O0tc/+jWRxXUqqkuO3FTew9mOexx9NICbouuOKSOh5/Ks1TO7PqhhbVWbcmzG8eTPL4E/cyPbmHpsYAr3jZi9jb3cnEpMORY0XaWm2EgHvuT5LLewyPVnjNy1qx7ZMTMj0fIqlLgD8Drp5jwnazEOLNQog3V+vcBuwXQuwBvgi8Qp7A1UZKJe93s0oPAOBXPLyCo5TK1Ra8vIN0fJxUTY7uJEtIKeeXpUpKBzKjL5DgpstsWmOzeqm65jXEda6/JKh0D1XLE7/i4c70WZVceQUHv+LNMiMAJ11GSsnU8R0c7f4Khfwgxewox3fcztDhX8/26aTLeCW3pkvx5+taToJOGfaeB71DJbqPlyhXVPWxSYeJhMP+I4VZvUZPX4lS2WdPd02Wu+ewsko6sFcp63wftm9PMz5eZnRAMVfX8RnpSzMxkiOXVvORz3oMHs8w1p/BKauDQiZZIjVVZPBoalavMT6UpVRw6etOzvY5cCSJlJLdT9zD8SPfoJAfJjk1wF0//iqH9tyjnsn1Ge5NMT2eJ1c1SiiXXMYHny7NOCE6ZdhnMw6TE0X6+7JViyiYGC+Syzr0HkvPyrn7j6bwfcnAkfk4lAoOY4NK7+B5kiNHK0xOlJmaUO+CU/YYHcjM4giQzzhMj+UY7k3N6jUSEwVyqTJ9PcnZPoePpXBdnyMHEnP6TFApe+x6/Hb6j/+AYmGExEQ/d37vs/Qf2Qao+R7tTzM5nKOYV/NdzDtMjjwr/dEpw356qszUVJmjRzL4VR3mQH+OYtGlpzs9W6+nO62w7VFrR0ro6UmTSVUYGlJr3HEkBw9lGRwskExW13jOo7snz+LFBsGA2n7rmoI0txjs2l+YtTQ81FMklfZ4cntNp/TUzixSSp7alZ3tc/uuLMmUy4MP/ISh/p9TLIwyONjPpz/3zxw/pmwA8gWfA4fzHOzOk8ur92pyyqF3oLY3nig9H1ZSjzBr6Po763wJ+NKzaV+z9FnGMEPC1NDMOXoNTSidgqnjVzcaYSmTPc3U8atKNmFqCF1TuoMZs1dTY3TCxXXlrMxvcMyd3z6gmTrSquk5EChTQUvDn7nUGBql3ATHur+Oikv2XaAZ+HPGRu4iHO0kFl+NZupo5oz540z7J8+7TzX28ej85aHrEAnp1EUNBkcVgwsFNExTUBc1yOUr1e+pE38kapDLqg2pscEkGjUwTDFrChuKWISj1rw+onGbUqWGhRAQCJuEY9ZsjE/T0jEtjXDMIp91qm2ZTI4dp//Y/wB1wA+AIPAahvpvJxhqIRJdTihiEYrM7zP0tDGcCJ1q7MNhg0i0dusxDIEd0AlHTFKpKvZhU5mDRy2yVcV+KGIpfGx9lunGohqRiIGmKeY9U88OzF/jwYiFU66tcV0X2EGDcNQiMaE2QTtkoOuCSNyiXCrOtjU+cojRoZ+j4tx9D/CAV9B79LusWPNmwpHFCvvomY29pinsozETRlSZbetYlkY0ZpLLqfUciZrouiAcNsjnVVk0ahIMGZimwKmu8bq4STxuIgSzG39DnUk2W8PZ9yX5nE9Dfe19CwY0wiGNxgaDiSm1xuvrDYQQNNSZTCVUWUO9ybFje5gYvw8V3/DbQAp4BX3H/pulq95EKLSAhnpjnt5OCKivO/nt/7SGN/9DpJkaRvXltrwQftHFiFrotlIaSyTS8ZVOQNewW8IIQyCrOgyAQEeESqIEGthVfUKwM4qTKiFMDashyMCox999Lsl1FwfYf8Th3sdKGBELqyWEX6j2GTDQbB0pQVaUDkMYGnZzmFyml6N7voNTGUfT64BWVLyvG6tP8nXgBnqP3EFr1wDLlr0coQkCHVHcdBktoGPEnr3y71RQLKLT2WrR0WLiupLJpMvqpUGiYZ2tmyKYJuQKPpvWhNE1wTUXx9m+L4eUcMG6Er4QvOglC9j5VIJAWOPaKxuxLI3rbu1g/84MkViA9qX12KbgvCvamB7Ns2CRTXtXBCPk4zkemUSJ9q444ajFsrVNgKBYcFi0ogHd0Fi/tY1H7nqAXY//N5XKFI/dX4/KWPlh4Krqk3wJeB3He37AOZuvZ9Gq16Bpgo0XdzI+mKG+OURLZ/R0wfxbZFka529tIV5nE4tbICW5rMPipTEsS2fDxibsgI7vOnStagU8Nl7cSe/BKTRdY+k5TeiGxpYrFjB0NEl9g8mapS66bXL1zQs4dCBFKB6c1Secs6WNqYk8HYvDxBuC1DUEkVKSS5dZsLQOO2hwznktCF0xoCXnNCGE4KIrF/Cr//sVe576Hp6bQtNiqMPRF1AXAIDPIOX/42j3t9l88W10Ll2FEIJ1WzuYGsnS1B6lvjl0eoB+BrJsjcuuaCMSMVm/oQFdF+TzrtJN6BpbL2xh/z4lplq3TunCrryqnYMHk9i2zjlr67ECGjfc0M6hQxmamkw2boyjaYIbrm/h2PE8HQsDLFsWor/fwzBKtNWXGO3NkM1EuWRLBMOARKLCxRc2YFkaL7qhkXA0jVP2uWSrmrOX3drMt//nlzy17f/YuyMP2EAM+A/g/OrTfBTH+RRHD32VW255HWtWdgFw4zX1DAyVWbMyRGvzyTPrM5phSM9Hev6s6MiveEhfoodNJSZKl5GenLVM8ko1UZVmG1h1Ol7ewc2UQYARNDEiFm62jJutIHShGEPQ4E+uDXHx5gCrlro8vL1Ez94nmDq2H0ML0rb4asKhFqTr46SKOMU0vmwgFIzTu+OHDPf8GvgOcBO+ez4qje/YnCcZByx8/ynG+pfSufZaAvFGpUDPOYiyhhGxEebvPTT9UalY8nEcn1JFsv9IkUzOw/clHS0m00mXA0eKlCuSaEinYUOEkfEKh48VkUBbk2BBOxw/kqP7YAbL0li3KsyiRSF69mcYPJYlECpS1xrFiBj0Hk6TGC+STZVp6mxg37bfsPfxHWhahEr5ZpraF5NLlxk8Nk0xl8Y0BSs3NXPHd79I9777UAYwl+L6q1GBP8fnPMkEEMTzHmb/9lVcePWLidXHGDyaVCKXTIXmzhiWrf82CKeBKhWf3uMZWlpD5PMOfb1ZSiUPzdCobwiQTJZnRVV2NE9sVYDp0TwjfWmEENS3hGjujDA6kGHweIaJEZ2OxiB1TZLuAymGe3OEImXaOmPohsbg0STZVBmn5BCrC7Nv290c2L4Xw6hDyhfQ0LqAdKLE4NFpKqUMwYhBR0cz//3vH6X/2C7gLmATvt+FulVPzHmaMaAO3/sJOx7dwtarXoQVMBg8kiCdKFHIOzR1RDCM50My/typUvY5diRDa2uQVEqJpSoVn1DQoG5TA5MTJXqPZ/F9SWNTgKVLowwN5ek9nsMwBG1tIdoiQXp6shw7lmNsTGfJkhCxqMm+/RmGh0skkg7rV4Wpq9NZtdIiHg9g2zr9I2Vu/8WveeixPky7mVD4BtpbGxkYLrNrV5JyOU9Lk8Gm9RE++vGPMDzcB9wPLAea+G3sR4FOPO9fueOOl/Kim69ACNixJ8fklEOh6LN0cXCe9daJ0JnNMHxwMooBzIiVvIKjmECuptdw0mXMuoCyTKpe+ypTBcy4rZTUABIq00U0W5/VO0hP4iRKbL2ugYs3K4uBRR0GRvoeuh+/F997G0JsZ3z049QdXUOlmCCXGQLUdTAY7aCY7QdM4H2ozIq3ol6i/0ApPFqBfwTeCTQhRDPFiSksOz6rS5GOj5MuYTedOactx5UcHSiTyrhkcgr7YwNl1q9y2HUgP6vX2HEgz4bVIZ7ck5vVazyxW/In632efEwZpFQqPo88nCAQ0Dl2SMlfSwWXgSMJmlpCJMaVaGN6osKPvvE1Du3ej+f+BUI8wPjIBzjes47pyREyiSHAY/9ujdivWskkB1FL+B3AJ1BRnfcCnwQyQAj4FxT+C4Egxw8Os2CZRmJCrYtcusxoX4pFq046I+Ypo6nJEuNjBSbGC5SqPioDfVmWLYvRfTg5q9fo2T/J8pULOLJvQt18peTY/kliDQH6Diu9RrnkceBgmZWrywz2Kn1BIecwdDyFFTDIVt+F5ESJn//PFxg4Mo7nvQohfsH4yAc4cmgN40P95DKjgM+BPRb3/F+MTHocdTB6Cwrjq1GM+t0oWY4LfB74BrAK6VcYODJBtC5CumqYkkmUGB/M0Lmk7o+A6onR0FCByckSPd1pKhW1oA8dSrFydZy9exJ41T1n7+5pFi+OsHeP0uW4ruTA/iTBuE5Pj1rj+bzH3j0ZFiwIMjysnnl6qsKBgzle+2eNxOOKUbYsiPCFr3yGbds9PO9WhPgx3/zGh9izawX7D/aSz00APgf3BgkGLXK5JAr7v0Td6C6qjv4NqCjqCeDfgTuAdbhuhj37c2i6YLIq3uobKHGst8jK5Se355zRDANQOoen6zCMqi5itkD5Ragyb/Z7Qij/jBkHOWGIWmgRyWxZOqtCTkxNpXj/+7/NT777S9QL8K9I6SClRmJ8e7WzWLWPCMXsCEpe/mpgLWpjug04ApRQ4hATeCXwd8DX0LQcgUjb/PHPPOcZRqGARvnp+gRLm1XWgfLN0HVBMKDNMpZgQIVEsQMa5ap/SyisEwhoCG0mlIqyrpmRo1fKCYYH7yKVeBy4AvgcUnp4nkNv9+OoCYsCeSBGJjkKRIA3AYuB9wB/gZKfl4DPoZb3W1Ev1r9gmmGi8QYsa/5twnwOPjCnimxbn3fr0TQwTG3e2C1b+RpZtoHrVKMZ2Aa6JdANMctYAgENKzB/fVm2Mdt+qTjO8OCvyaT2AecBn0VKH9ctcuzgY9VvBIEiUobIpKdQN7n3oE63r0fh/BsU9v+Isqf5EPAi4AMEQ8sIhIJYT7MEfPrn001CKOztOdgbhsAwBIGATraqM7OroTssS6Nc1fvYAaXrmKsrCgZ1gsH52IdCOqWq3nPPnqP8v7/5Jo8/eQiVNfWzyljHyfDktgRq3VtACc8LkMulUCKov0PNyZ+gUl98BfVufLzay+eBC0H8DeHoGkIhHe1pW0wodPK36jNrtp5GwhAYVaWY73j4JRcjYs06vklfIh0Ps76qw2gNU5ksKB1G1Y490B6hMlVUOoymEELXCLRHcJIlhKljNYY40u/yiS+P8e+ffB+TEzehJmg3sB5Yg0popVXLXo2Sk2dQG9hTwAuA61BMZj3wt8B/onKiBICXAFHs4CJWbHgrwdbY7HjdTBnNNjCfgwPTqaBISGNRp82CdotC0Wc65bJqaYC6mMFF50bxJRSKPpvXhjF0wTUXxXhsVw4pJRdvctA0wc23dLL98WnskMb11zcTDhtccVMbB3amCUcDLFrVQNDWWLbW4vbv/htO5SWoHC+HgU2obJY/Qc3HfuBK4DKUdWQd8DDwUmALytn3OpT+4lOoRGiTwMuBfyUcXcHWK97D0nNa0A2NVee2MjGUpa4xSHtX7I+G6x8iwxCs29BIQ2OAWNzCqfjk8w5LlsYIBAw2bGrkwD6B57osXdsKSDZc1MnRfRNousaKDS0YpsaWyzvoPZwkFjfZvA7MkMklV7fRfShNKBagc2kdmiaYXDTC3T/9Ep77EqAb6AO2opjxXahb2g4UvjejMG0A7gNehdrkllX//jjwflQeoJ3A64CPEIuv4cKr3kHXCuWLs3xdM9PjeRpbwzR3RP544P4BMk3B+VubicctNm5qwPclxYLHmnPqMAyNrRc2s2vXNNKHDZuUn8llV7Sxf28Sy9Y499xGgiGDq65q5eChDA0NJps3xzEMjUsvaaC3r0BbR4DVq8IcP+4yPjbAK1/xtxQKL0Ct7zHU+nZQ6zeGYsIbUXvMJIpB34O6TbSi9EZvQ93y3oF6N+5EHaTeQVPjel58y1+yYa3yw0imXIZGyqxeEWJBx8nvOWc0w8Bn9ibglz28socwPQwpkZ6PX3bxHR+97EG4Gjak7IKvlOEElLjHL7sgBNKVYFZNc8semi9JDu9juOcXHH8owfQUSPkwcAvw58DPgQdRL9DjwLuAfSgm8GFU6JoHUel8r0MxEA9N/x+QLlK+D6G1IESWNRd+CNNtQTM0pXfRwS+7eGVPPaIv4STliaeSHFfi+Sqw2mTCYTrl0lRvwGKl35hMKDloKuPS0WKRzftMJRx8Cdmc2lJSyQqTEyXsoE4+7xEOGySnyqSmy7gO9Ox9hP1P/ZzJsRGcShT4Ncpa8qUoC7PDKMuPPtTmMwKsQp1ct6GwfwzFMGKARDf+Dd/XEOLtaFoIw/C54qbPkhi38RwLx/HQdEE2WSKTLKHpohpo78zA3vMk6VS5esr0SafK5HIumYxDWzuUSh7pVBnX9cnnKjQ2mBTzFTKpEpomKBcdAjGdXLpCcqqEU/Yoly3MECQmS6SmyngeHNhxL/t3/IqpsVE8twMlvngzcD1KnJpBYVpB3ZpLqO3iIyhm8QCKkaxArXsNXf8kvm8gtL9A1zxM2+ay675AYkLDqdi41eB7mZTC3rR1fF/Os945neS6klSyDEuilMs+yUSZYtEjk6nQ2hYkX3BJJir4UpLPucTjFtmsQzJZxrR0iiWPIAbJZIXpqTKe61Mu++i6YHKywuRkGcMU3Hvvr3jy8fvJZKcpFJYBvwDei9pnPoOyNPNRYqdbq6OrR93ibkdJLQ6iGEYUsND1v8f3DTTtVRhGmlisnmuu+wR9AxqpjK0CJAoYm6gwPlGhLq6cjmcCLZ4ondEMQ/qyGsRP4hXUVdDNlJXiOleZNaGtTBcxopZytKuKn0oTOSLRBkrj+aoJraQ8mSfQEaUyVSSV3Mdg7//hulngIlI4GEYvQhSQcuZGcRWKu3uo0+4MuB8HDqFuGi9AKZ8eBd5HtGkVrS1XEQosJpM5AJpH85qP444qOZhf8ahMFzHrA7O6FL/oUkmVsBvPHB1GuSI51l8ilfUYnVTY7zlcYPmiADsP5EmmFfYPb8+yfFGAR7ZnyBUU9g88Bbeskjx47zi+rxyi7vvNFNde18zuJxIkp7ez4/E78LwCKsNkFssaxHXb8f0voXC+ElgEdAFx1MtRAT6IuumdgxKf3Ie6jbyTRSvXETAvwg50kEkdJBjRufi6L7DzoQTgk0mW6D00TXN7hJE+ZVM/PZZnuDdF14qGUw/qCZCUMDiQo70jzPh4YdaEtvtQks4FYQ7uS8yace7fMc7ChZ0c2jFGpfouHN49ztarF3Bghwqcl5wus2e/ZNWaCgf3JkhMPsGOx+/E9x3UaTaJbffgOOvw/X+qjuJS1El2CVAGVqMwfzvqBngx6hT7G9S8vInla9ejcz6W1UQmfYhYQ4DNl76evY8p7FNTRfp7pgnHLCaq8b4mhrKMtadpO0NueFJCT3eGhV0RerrTpKv+Qbt2TtO1KMLO7dMUqn4r25+a5IXtXTz15BS+LymXffbsSrDlkiZ27lT6o4mJMjt3pVmwIMDh7jRT4w/z5CO/Rp2CLwUShEJ7KBavRsq/r45iK9CI2lsmUSKnAZRk4yBKxHc7at07CPFWLr5wPVOZ8zHNGNlMN4u7Ornmqj/np7/IApLe/hK79uXQNcHxPiUL23sgz6rlIZYtqYV4ORE6oxkGKJmifLrJ9Uxk4adVnM8sa/GJ5Nw6wPDAL5gYewLFnf8RdZvwkfIylNL0UtQVcSVKgTSGUlr/GvAIBG7k4osF/f06Q0Mm5bKHZb+BuoaVLL/iTZQG8kjXp75hM5qtYwdjuCSfPrSnDf/MOGXNJU0TPP3wpwnmyUKFUGOfe0rUqi4mmiZmnZ80TSCEpP/4j0hO70Xd0v4LdZtz8f21KPvxLSgd0DogBwyhdECPAT6h0DVcfDF0d2tMTJhUHA3LOkRT6zpe+oY38dAdx/Fcn/rG82hoCRGK1KPmsPZM4mkPdaaccOeSwv5p4xRiNuz5zGeYH0J/tmyO3b+hgWFIjvX8N9n0EdRh6C7UOi/j+4uBJEqc2o9ixBXUQelGoBtNcwiHr2PrVti/XyOR0HDdEUzrYTq7tvCS17+O3/zkOL4vaWg6n/auCJFYlLnYm8b8cPigPtsnH9LolNLTsa+t8VodUU1JMFdfITR4+musaSCkT8/B/6CQH0TdHJ5gZn1XKh0IMYKUq1D7zEXVOgtQzPgwhpEjEnkB558v2blTI5ORSPl1DPMnrFp9HX/+57fw5a8PIyU0NF3AsmURAoEgUAsaqWvit3QYJ2shBWc4wxC6wIjbykqq5OJVdRhGyFQ6DEeFDrHqA2iG8sMojefwnBLJzJNM7MgTbVhJ2FquFOMxh96932Vi7CHUC1GHemkAJJo2UrWC+FPUNfGnKLngRnT9g+g6mCZ88pMOGzeqhfKWt0Bvr87K9X9OtLMDXTcJtIUpTxRAqFAhQhfYbWFlpWVoWI0hNFPDagziZMpoto5Z9+wD4J0KCgYEi7psOlyLqZRLIuWyalmQeL3J+ZuiFEo+haLPeRsiCENw2dYYD2/LUKnkMf2HuPPHFstXr2NsuA07qLPpXJ8f/+ArJBMHUFftAjV7fQ9Nm8Z1iyj/lVuBb6HEfu1o2j+j6+pl/NKXiixZAq4Lr389TE1ZbLroQ6y9aCEi7LLusiaO7EximBorttZjxT1WXdDAwKEMoajJok0RrIBO13SMiYECdc02basD+PrJe72eCtI0WLYiTnNLkFjcIp93yOccli6PEwwZrN/QyO6dU7iux8oNKnfDugs6OLxrHM/NUCg+wSN3uyxcvoHkRCPxOpPlyxLc84vvVi2dmoDj1CxrHIRI4/sZlGn4VSiDgZ1oWhApvz6L/de+5tLWBqUSvOpVKozJlks/wgVXd1AXd7ngykb270gRCOpsvqQeI6izdks9fd1ZYg0WqzZHMQxBOhFlfLhIa2eQRatshHhukZqfL9J0WLE2ihGRLDknTLZQoVT0WLEmSokKazbH2b8jhfQl55wbJ+uU2XhBPYf3ZfC8BNOJB7n/HknX4k1MTzcSixuE4hP87Oc/oFBwUOK74yhmAVBGiCK+fwz4P5QPxYeBbRhGHs/7P3RdOcx+4xtQXw+5HLz85WAYAS68+M1cd5kFlTGuvFCwc78kHoVz1xQIBYuct15wtE/S2ixYsVDdqFctFYxOSJYvFjRFp8n+3ohyv01nNMOYJUH1BlE7HYrqLUMo9j9b1fcdDu3+ApXyuUh/K4b5Vf7mvS/i6usv5WW3vJG1a7KMiMVIOY4SZXwO+DLwY+rq+sjl2ikW31VtbQm2bQCP4fvqxOb70Fi1wNQ0WLMGgkGfqy95gs9+7FXglEG3IKwUkuST4DlghiHUAb4HuWmQDgTqwQ6DW4G8Oolp3z31cJ4IKQuQCpoOliUxTbBtD8uqYLs+pikxXbAtV5XZHoICTz7+WVznKjxvJZb9ZT73r3/BxvPO4cU3vonVq/IgN6FuEBei5LX/CPwnLS3TJBJrKBTeUB3BKmzbRYgncasRVHQdGqqSI8OAlSuhvt7l6kv2cekLNjKVhtYLg2z+uyYcF544IMkV4dYrg6xZ1Ea2AI8fkDguvPqmTha1CiaS8NRhyR8OGvHHIXVqdfD8nEqNpHloukSISrXMQ9N9dCSIIp4EhInrJtnx6L/gebfi++1Y9mf5r2++m8bWFl7xkg+welUJKa8ADgCbgc+ijDM+TVdXkZGRSygUXlIdxQYsK4+ub8ep7uWWBXHlN0YgAMuWQS5X5gXXH2XVeauYSvhcsLaej72vmULJ57GdLuk8XPuXzaxa0kYiLXlkp4Pnwa1/38GCVo2hcZ9t+1zOFBJASLhEvSKm9LE1ia9DWDhEvSK+9LB0iRSSCBWink8BB7c8wfYnPofnvQYpo9j2Z/jRjz5EsSj5q7/8O5Ytr4B8IUr/2YRy5P1LhPgAK1a4HDv2IsrlG1CykM1Y1pcxjCSVarSgYBAiVduASAQWLgTXzfGyl06weMFG8nmPV24J8KGVEQp5j907UjiO5N3vitC5MEBiusK+3SqEyac+GaOh0WJkqETP4ZMPy3JGMwzpSeV0J5XuApS+Qg8aKqdENSZNeTyPHjIpT+RJjGzHKS9G+j8GBK5zG1/83PkEjCxXXp7nBS+Axx8fwjB8TPMOisVG4JuAy8KFsG9fGnU9f5Bw+FW87nVFkkn45S/hy1+GO+6Av/97+K//goEBeOghuPFGyXQyA5FmSA5BtBH06j070gDpCYg21RhbqA5KWQgrb1EMCzwXSs8qptEpoUJRcrTXJ5V26TmuVu4j24q0NwfYdaDEwLB60e9+KM/rbgvym4ezHDz0KJXyRUj5HQAq5ev4+D+8jJe97FxuvqnAunXw+ON7MQyBaT5Ksbgf+FfAoasLJifHgTxCfJ9Y7O289rUlhocVxl/+Mnzzm/De96q/u7thxw64/nqfciHDVecKtu9z2LrJnM04duVGyZE+l/PXmSqkQgwMfBJpn/XL1fzUR0HzPcanfM4E8jw40l2gpT3E2EiJsWoIln17srQvDHPwQIbpqi393m0pbn5JMwe2TdPbcz+OcxvK/h4q5a184qPvZfPmBl79qhLBIGzb9gimCZpWoFz+DPBhhHBYuBCGhweACpr2eRoaPsqrXuVx7Bjs2gVf+hJ87nPwgQ/Apz+tynp64MorfdxKnmu36uw9JDl/k4muCRrRuPJ8wdF+n4vPVTg31oGOJF+QrF+ltp2GOg3hSyanzwxu7XmwZ3+RpvY4R3qyjI4rnJ/YnueFt9SzbfcEyYRa90/sKHLDTe089tQQx3rux3XfivIFgnJ5Nf/4j18hGs3xlrdWGB+H3bt/hWGApgUol98H/DWG4bBgAfT29gA+hvE+Wlu/zG23wb590NcHn/0s/MM/wCc+AR/+MDz6KExOwpYt4Pklzj2vngM7cpy7RVm9xetM3HIdE8MV1qxTEQxicZNyVh14Fy8Nz5YVUpLU1Mkx7OeFYQghbkR5kOjA16WU//S0/9so29TzUHZfL5dS9p1I2zOpTp9e9ltxxKQq8/0yUs5VUHdSqeT47nfvRAifvXshGHQ5/3y47DKf739/jIkJdd3r7oYtW1x27dqEruf40IeKbN1a6+LOO+EVr4Cf/hRuvFGduv7sz+Cuu2z+5dOX1xjCXEEzzyDYfCZh57PUYZxK7JEOUs7fSDVRwfdrsfw9Dyyjguv5VexXzKndTiYzzR13PEAoJLn3XnUbu/xy2LLF49vfLpFOQ1MT7NkD55xT4NChzQgxzKc+VeScc1Qr5TL85jfwylfCW98K11+vTl2vex389Kc2//2dCzEN6IhI5rqzBE1oi8y3BIkGQH+aBKQhCHrk5DetU4m967q4bg17KcH15pd5ro8UEs/z8TwHZSAwQ62MTwzx0EO9NDdDfz8EAh433qhw/vrXC5RK0NIC27fDkiVTHDu2Bd8/zOc/rzYyqG1SL3+5YhjXXQfRKLz2tfD975t84IPnYeiCeFDO03fZpiBkz8dU6TDmP6dlgmmcWdhHrAL6HDGZ70N9MK+kAzNlnkdjOI/nyWfAvpnjvUdBZkgm4eBBdTu/9Vbo6srz9a/ncRzo6FCHnra2XoaHL8J1n+JLX5LU1cEtt8B73gN79yrs//mfFfb19fDqV8N3vyv4whc3YluSxkh5nh4uHPCoj8wPZhoNub+1Z9aFHfTiyYlin7O3mBBCR8l0bkKZrrxSCHHO06r9BZCUUi5HeZT88wm1rYEZD2DG7NlESEbUQg+ZKs+EpbSrZkMAzdSxm0LE6tcgxB3Aj4GjWNZWFiyAN7whwcaNMD6urtQf/jAkk2rDe+974SXV2/ixYxVcdwAhEkTnhBiKRsFxYP9+pccACNgmd/w8xLve+Xr+9GVXzIqVyCfUKvM9KCSVp1ohpX57DhRTSgxVqrJ9p6z+PoOwt23B+g0Btl4QpK1FR9fg3PU2i5bYXHFpiLqYhqHD1ZeFiDUYXHdliJaWdWjaN4FfAj3Y9hUsWlThzW/O0tWl5K9NTfC+96nbWTgMf/d3cMMNil8ODpZw3R4g/1vYVyrq1KVpShyl6yY/+1mMj33s7Vx91XlMjamT0tS4i+9LXEcyPeHiOpCcUmWVsk9q2qWQ98llPKSUFAs+mbT3TBCcFuyFgCVLLVat0Dl/S4C6OuVwtWFjkIXtcOFFIUIhDcOArZfGaIgJtl5ZR1PLWjTtcyjrmUMEgzeyZHGOt7+9QCikdD7LlsE73wkHDkB7u8L+0ktVn2NjRTxvH1I6z7ju9+5Vn4NBDSFsbr+9ji//+9+xefMqxidcihUYGFThY0olSf+wR7kMYxOqLJf3mZj0SaUlyZRylE2m1GfzJE2aTyX261YFWdIa5NJzo8SjOroOl50foT5gcdXWKMGAwLKU31FYM7n64hjNLeegaR9DWUruIRR6GSuWJ3jPe8qUy2q9bt4Mb3oTPPWUEqV+4AOwaZPaf1KpAp63DZCEQrWxzGC/e7faJiIRnUrZ5M6fN/Cd73yMZYs7SR7LYrkw3atCllTyLpmBAn7aJTteRPqSYqpCaaxEabxMMVVB+pLseBE/5RA2Ts557/m4YVwAHJVSHlcPKr6PMn2Zm1/3FuAfqn//GPiSEEL8oXDDTS1WVWcheOPb2lm73OKBbSXueqSIHdJ5+98vpKPF4Cd359l5oEJjq80H3nk+Rw9/gA+89334ziDg8JGPwJIlMDysXprRUbXx/OIX8P73w+rVqr+JCSVyuvVWNVn/9E/wt38L6TR897uwYIESTZmmyTf+/a947W0XKq4WqoNKSTEBANcBp5ojw6ueVNwyOCXFRLzqBuWUlKbNdWruz2cI9p3tJk1xlR3ti59pIBrTGR4oMzHq0Fhn882vNmMHNHqPFEknPS7aEuS1r72SBx4I8+73vJliaYxy2eETn1A6n3371IuSSKiX4c474d/+DTo74aKL1PX7scfUDa5YVFfwd74Txsbg9tth0SJ1SjYNkx99+4NsvOBCfE9S32RSyPtUSupxyiVJIefjV3N1AJQKPpatIoh61Rt4Ie8jNCgV5LOE/tRgv3yZzQf+XwdDAyon9J++uIFwRKPveJnJCZeVnTZ/9ZpmdBMOdTsU0yVWL6vjb9/yQu64PcqHPvA6yuUxikWXT35S3cQeekhh7zjqHPOrX8GPf6zW+IUXwuHD6nb9hjfA0aPwkY/Am9+s5uS+++DYMRgaAsOwuOP7n+Dci9djYGAENApFD0P4hIPgOz7ZjMCpSEzpo1tQLvjkclAqSmxNYmtQzHvomkYx7xM2n5U46pRgv2ypzWte18zxXodYu8W/fXExoZDGnr0lxidculaH+MafNaFp8NSOIpmMz5ZLYrzpr1/K974X5l/++TZ8bxLP8/jwh9XB8o471No1DCgU1Br/+c+VdGLrVsWIJyfhbW+Dhx+Gj31MSS0OHFA3v/FxGB0Bwwzwrc//A2sWLcYM6TQujlJIlHGKai8ppR0KiTJu0cOrhlEqJMpouqCUcWZTA+QTZXzXp5B8VukUnheG0QkMzvk8hDImfsY6UkpXCJFGGRv/Xh19c73G5z67BYFkc6uKNXzRuQEuecG5dEQyrKhX+VAuPDfIPf0r2dQyQns4y50ZB7xehJBoWm1/zuUU0wgGlSx25gWaIddV4o63vQ22bYPvfQ++8IUGmpvreN+7tqAZJnUtzVx99bmsXtUFyWGlh7CVXBDTguSI0lcY1UiQmg6ZSYi2zLdHLWYhUtVrWID0oHTSSqhThn0gqLFxlYkZ0Gms2mo3t5oM7c4Q7wwQa1Veok0tBgPb07SfEyYQM3FljkJhEKHNNzlMp9XmX6kombjvz8fe9+G229TLcu+98OtfCz73+XraWhv48HuvoOy5tC5o5Nprz2PZkg4G+iq0dpiEqqkpLVsw1OvQvsDEqJpu6jpMjrm0LjBnr+zSh0LOp6VdXRPDEeWwlc+cNNc4JdibpuDc88L4pRKNLTaLVyjrueYWk8fvn2Tl2hgt7Qr7xgaDRx6pcOEWm0hYo1ScplQamrVqmot9MglTU/Ctb9XwniHPU8ziRS9SjOQ739H47Gfr6eho4uN/fznZcpmupW1ce+15dC1oIZUsEYzp6KZGALAMjWzBoWuROesAqemCqUmXrkUqJHcspvopl3w6OhX2sZhOpVwhlztppnFKsLcswTVXRQg7CRYuD7JwucJ+QYfBw7+YYtMldTS0qPe6tVHjyXuTXHZTHDuoUyqM4bljGAazBjIz2Pu+Ej395Ceq3JtzofV9ePvb4fLL1fz88pcGn/1snK6FbbzztRshCqvWdXH99efTGI8zsG2KjvX1mEG1dWumxsThNO3r69Cq8lgpJbmJEi2r4wghCDcFcMseUkLTUnV9DDcFqORdytmTs1A745TeQog3Am8E6Opq5bzI/qp8v676f7givg3sECpCIxia5Ka6+8FupLt7nD97zUf40Icky5bBu9+tfi6/XHF424ZMRp2cmpsVR/+rv1Jc/vbb1Ri2bYNczubXd/0zV1yxSRVmp8AMQGBOKANNVz+zg9dr5XPrzBhsP/17c/UW2umfiqdjb5kehjXHHl0TWIaDadZCCuiGhiXKGFaU7dsP8853fIZPfFLJZ9/+dnjjGxX2ExPqlJXLqRNuXR188IPKNHZgAB58UMFx992CcjnIAw9+nvPOW6U6yVTA1tVPlVRspdrYZnKZ6HNg1A0V52qufNcwxG95dRun2cv76bgDdEY8QuFaHV0XdIUcYqHaWG1bY7mZI2TXce+92/nUJ7/GZz6jrJne9jaF7eWX10SvAD/7mbrxvfe9yjT28GF1yj14EH74Q4H0ozzx5L+xevUiANyhNFpjCC1YUz74mQwi3lwbmyYRuTy6UVsXpu6he2WUKqFaJhx8PNQJqVqGA8VaErI/Nj0de00TxGxJOFjD2bQ0opo/LyZUIKgTli6WrfHDH97PN77xA774RXVzmMH+sssgn1dMQdOU7rO+XokC/+RPYOdOtfY/8xn46lcFltXA7j3/PrsGjtw3SNcFbdjVXOkztwRjbpwrW0cztFlmMVOmV+OMzS17+t3KsDXKJykJfz52qWFUKNAZWsBsqpvfqjMkhDBQrrvPmC5RSvk14GsAW7aslJSrmdzssLI8ckpK3OO7agPXdHUy910oZLjvNzu56CLJBRfA//yPmqyXvERNzuREAM+TbNpU5okn4POfV/LBhx6C7sMa73rXK7j04nOIiCIb1nZR37VU9e2UoVJU4iUrqPos56v6iIy6TQgNisrWmUK6ZgFVSKtjbTELwagaUDGrRFSVomrPc5+VDuNUYn/e5pWyMKVykIeaghi2TjFRopJ1yA7nsWMWmqGRHc7hu5L0QI67fv0UN97osmkT/Md/KB3FTTfB449DqRAjnSly3nkOjz0GX/mKwv2+++DgQY2PffyvWLV8IfVWgI3rlhJbUMWv4oMj1Q3M1JTnYMnD8yAx6dLSoZLTJKbUjpic8mhoNvB9SWrKw6lIsmmPaFzHcyXppCorFnyCIY1K2Sf3LHQYzyf289f8KlmeyuAeP05xMkC4YS16wCTfP4E22k9OZrC2rkQzdDI9gxjFUTJHdX5x5yO89KUuq1fDv/wLtLYqUd/994OpNTA5keT8CyQ7dsDXv65Eq3ffrZzwvvDFd9EUCxPLl1l/zhKal3YC4KZylKam0MtBAotVwMzKWAI3XSZvpIksqAMJyf4Ufq7ExECOlq4InuszfixFPlUm3WISbw5SKblM9qZwKx4NzRbBqEUxWyExkJzdCM8E7BNjZZIpH+9IiVizjWFpDB8tUPI0+g/nWXleDCGg/1AeVzcYOJznzjse4NWv9li6lFnx9+bNcNddEA+30T82xgUXwKFD8O1vq5vGXXfB3r2Cb3zzg7hlsApB1q5dQEe7YsSpkSJuySPRl6PtnDoQkOhVe8R0b47GpRGkhGR/DrfkkRktEGsP4Tk+qcE85bxLMVUhWGdRKbpkxlQk71h7ECtkUExVKCROnlE/HwzjKWCFEGIJapJegYpENpd+jgoG9DgqMM19J5IuEd+ryfYLacUgZhjIzGatmcyySadEXUhnfFyjXIbvfEeJlRoblVXHW98q+eT7/4r//dnjmOYO3vY2xemF0OnsaOcj77+NgCFrfRSrfVYKgKz2mVZ+FqVanxQz6nYx871KQR11pazpMkpZQIDvKGYx077vqc/+s9q0Thn2XsVHehLP88gMZrGiFvlxFRK8nK2QGc5h2Dq5MVVWTJQIYDIyYpBKudx5J/zv/yo5+atfDX/+hjLf+cLf8u/f+QW6voe//mu4+WZwXZMNa5fz7re8FEMKxSAAiq5yUa6GvMCVUPSUmUY1Omg+55OY8jANyGdUvWzaQzfUibpYDVWSTqjreKUsqZTVo6emXJyYTjHvzxMRnASdEuxzvVP0fPE+6jcsoJJw2PGO7+NmizRs7iKypIl8X5qjX/s2vuPQdt1K7Eab1M4e8g8eZ7RdMDQkeeopdVgKBOBP/xRe8+os3/vIX/CZH92P7x/jne+Aa6+DYt7g8vNW87pbrsDLlHHTymKmPJpBDxr4edDtBnDATZQRhsDLemBHcIoGuYkyjpQU8gZYEaanJcIoUS755Ao20rQZG/Jw3TL5rEfJDYEGowMO8UZJetrF1aLPxvTmlGDvlH1GD0xhVcqUJ2D0sI8dNpnqTmM5DrnBPGNRHyE00n1JLMcncayIrQUZGRYcOiTp71dOdoah9pZXvXKS73zwnfzT939GPt/P3/yNunmkkya3XHs+V2zZRGK0hJFxcFIOE31ZrIBOtmpOXUhWSA7m0QxBtppiNztexAho+K6kkFD1UkMFtcaLLuVqVsBEX45Ia4BiqoJXfa8SfTmC9Ra5idKz0t09Z4ZRlQ/+NSrWgA58Q0p5QAjxMWC7lPLnqBgQ3xFCHEXFCnjFCTWuGWBWY51Em9RvOwzpUTBDEK6rlgUhNQLhBl7yyhv4wld+yvvfr3QY9dWDqq5DW5uGL+HHP/0XPAnf/tav2bNzHzdfVc9b/+bPCERCMw+lGNW8PscU85i5OVgh1WcoDoGqWYkVgNSo+p5Z9dw2TCXOirfUxE6apm5FsZaqCW5VzDXDcE6QTiX2RkDHipqYQYOG5QrnUFOAsZ2TRDrCxDrVmAP1AUZ3TNC4so43rn0x3/je7XzsY6NYVs3ZyDShucXADkf45T2fx3E9vv6fd3J4zxFedmMbb33fyzECVTFFpqJkU9VrOLYGqapIKlTFz5aIhNJhRGLqem4HNUb6HdoXmljVxPamIZiecGnvMmfDIAihdBhtC5VvRqxOZ2zQoZA/ubfnVGFfSeQ58Klfce7HbyG5d4je76uw+sN37OX8z97G8e89xfhDRwCYeOgYWz53K/s/ei9bevJ85JDG6JhHKKSYBSh9XX29QSRs8uCT/0nZcfjKV27n8BP7ecVlzbz782/BMAxkiyS/fxQ9YhNcpLwjpedTODyB1RrFbFLvoRbSSR2eom5pFKuaQjZga/QfSrNsTSNWNVy9IXKM9eVZvr4Z3dBobAevnKKUd1lyTkz5xbRaHH5ymlzq5OTopwp709ZYfUU7e+6aoHVpmM416r2u6wiz65djLN3aQEOnwiHcEODgA1OsvrKFD218AxdufZTuniyxmGIWALGYCiHevqidbXu+Rb5Q5Mtf/hnHdvfxplcs420fehmaptGyWNL7+CTxJoPWFco7sq7V5+j9WVpWxoi2ViNvxyyGdkzTsaF+Vkxl2DqTRzJ0bmpAr6Z51oQgN1WiY0M9QhPE20OMeiove9s5dWpsrUEGd0xTyZ8GPwwp5S9RtpRzyz485+8S8LJn1bhuzo+9JIS6VRhzDLo1XZ3wdRPbsLj/ga/wrW/+io9/7Kt8+cslXv5yyb59Sk576UWrQdPRgT//ixfAa66Ccg5mmMVMn3PZrxCqTJ/bp6b61a3535v7e3b82nwdhW6pz3P9NeZ+5yToVGIvcZnr2KDpGq5TRjNrwnXD1iln8xiBJoKhAE88+V987T9u51P/+C2+9a0KL3yh5MknBaOjgjVdLQhNw7I03vq2P6E8msDN5LADNTl3OZtXoVJm8lkLQTmbxtAj6DPLVRO42TRGey1goGlBJjmBuWrBbJlueBQLCXS9fbZMUMZ1igjRNFvm+3kyyZMXCZ4q7KUnyR0eIXe0lkHNzVcoHBsn11vT2RZHUnhjKfL9SaLofLS8mId68hwVk/zoRx5XXgn33y/wvADLF3ep0P66zbvf/aek927Fy5cwqrubEALPl/Nk4ULX8AExJweHZpv4FRd9Tn4NM6gjK94sswAIhg0CpoY+J5teKGSg+TW/GCEEoaBOYeLkRSOnCnvd0AiEdULx2vtqBXUMSyMUr72joWqe7mDUpCvayo6d3+JfP/MTvvwfP+CXv/Q4/3y4806NttYmFi1tQ2iCSCTE+973KlLdCYShoVX1mpousEIGgVhtLzEsDcPSscJzxlE9MM38BrDDBoalzTILACtsYOWNeTHGrLAxT4chNIEZ1E+aYTxnP4xTTpUClAs1kY3rgFtSm/wMApWqTqOUpVQsc9dd26iPmNzzkw+RTKzizW+2+dGPWrjzx/9Ae0tM1Qf1/XJO6ShmTGJ9Dyp51e9Mn56jRE/lfI2ROCVVXpozjhkrp7nWTqWc+k65UOuzlFP9zfbpn/Tt4lST9HyKjz1J/tHt+GV1AiyNTuNse5Ls47tV6lwg2z0A+3eQ3n6QbLbA3Xc/RUO5zPf+4ma69y3gjW+0ufvudn704dchHn+U8pBKXes7LskHt5F+aBtuWuHllcqkDx8lc+g4vqMWspPJkz7cT7ZnEFk17SmPJ5FDo2SP1dLgJo9PYY5Pk+xTYmopJckjY/h94+QmFTPwXZ90zyilo6OUs+p675Yd8j0jmOPPqNY5LRRoDBNb0EDThgVoptqEY0ubCISDtJ63aPYA1XpeFyJfpm1rF3k8DlLgnDUd/O/bXs5jD3fwxjfabNu2iB984h2I0QSVKYWDV6qQ33GEwt7juLkqDrkS+b4xckdG8J1qFOhEnsLABPnj47MOtMXBKeTkNLn+WjDN5JEpxHSK6UE1j74vmeyeJj+UID+t3jXP8ZjumSR1bIryTISGvEPq2BQy96z0d6eEshNZEoe7Gdl1HL+6xqeOTZHvP8Lw7v7ZeiN7hyiPHWP0wCgTE0keuH83XbE4n33jG/jFHa288Y02x44u4xvvei353QdxktU1ni+Re2I7ucd34JXU+59P5Jncs4+J3Ufwq46ZmcFpMj3dTO3pnXW4Sxwconj0MNOHlLpGSsnUnuNk9h0gO6R8wHzXZ3JHD4md+ykl1Z7ilhymth9kevtB3KLqs5QqkNh5gOLRwyeFjzgRVcLpolWBkPxGq/KgdIMhzK5WnKNDGFXfBi8eR2+px+3pxxCSvOfxzulhGp0Kjb7PQ4ArJSuEYBTYaAWxDJO89Lhl5SoC+TKHpyZo1A0ujtZjL1uAOzyJnq8CHQxidrXhHh9Gr2Y0c6MxjLYGvCMD6PjKu7ylGT0SxD82MBuhVSzqRHoeYnisenoDY+Ui3EQWPaEm19MNjGULcIanMPJqQV060L1DSrnlj4v0b9Oahkb5g1tvBaCULyNCJqLkYgXVKahYKKPZJrrrYdgmU/kCf3nnz1lcqRBAZatwPI9lQjAMXLF4CY6uUfYqvHLTOgQ+h8anaI/FuLKrAS/SgqFJIp11YOpkh9J4no8dsQk2KdlWuncaBAQbQ1TiDZDNUxyaBk0QaK1Ds1Re98pUBt+XhBY0IjRBJV3AyxWRPoQWqkBg5aksfrkCuk6wrQ6Ate/56GnHfmUoJr93y58Q6VBjmto3SHEiS8uWRdjxMFJKxp86jlt0aL9wOWZQMJhM89pv/5D1vodnCPYicF2XRQgGgFu3nkOyWMYp+7z23PVk8gX6c2mWNNdzXrwBPxrHjkcJVXFI946B7xNY0EigMYKUktThMQSScGccIxLGkSaJfQNIKQks6VBK+IwDYxMgwaoqzp3pLFoug6eZWAtbVNlYAq1cxLeDmG3qlnj+W99z2rFf3dwiv/bCV6CHlQjIS6cwbA0XGz1gIz0fWciqrJF2BM3QOT42xt/c8X22+pKUgCMIXNehSwh6gVvPPY/hbAbLgzecdy790ylGnTLLG5tYG6/Di5o4eoBgOApUcJMZDA1kIIowBJap404mQBPo8TiaZeCXHfxsBt+TmM0NCE3DyRURlSK+I7Fa1Rp3Ulk038HzNaymOgAqUyl0zcfXTMw6JXI7/6MfO2Hsz2iGsVQE5H+2LEKizDJBSYc62pVzV6J6yJGaJN1Y4qOTw1yGz4+q3/834AOo1C8uKndYB0pjcBh1vXoFsAOBTYC3swANQUuzkhaNj9f6bG9TISqmq87cuq7GkU5DpnpAsixobxNMTEqK1UtMOAyNDTAyymwQvbq4ku+PjNbs4ZubIBQSZwzDWCoC8n9veSmVbInB+/YDoAdMVvzJBSS6R5jY2YtEoseDpC9cwAfv+jUvweerqBBqH0aFdXRQ2NuoRKo2CnsbeBmCxzRBqx/iL2lHaBrr33E9ruNx6Mv3qj5DFud++FamtvfS9+OnAAg0R1nx0Vcw+p0HmXq8B4DY6k5WvvV6Dn3+F+R71WJpvXItHS84lwOf+imV6mlr0SsuJraygwP/9DP8ikqstertNxJd3saqd/zdacd+qQjITxlLWHnbueRG0gw9dBQAM2yx6uXnMb69n8m9I0gkdkuUsc11/MOv7+fNSD6BCoz9NlR0NB+FvQUsR11MjqKC+r8YeEDTWONHeSWtCENjwzuvIj+c4uj3d6g+YwE2f+hGhu/tZuiuQwCEF9Sx4e+u5/B/PkFy9wAA8XMXseAVF9LzubtwxlMA1F+7ntgFyxn811/iF5TIqeWVl2A2Rhj+yj3g+aBrdL75OuyOei76wIlvWqeKloqA/JS9nI5XXkOue4DU48oP0KiL0PHKq5m+fxf5w4NIJGZXMwdW1vOle3/BB1GZzD1UIP6foBQrDmqdr0TNQx/KEeQGIbhLCC7267iFJoRt0vHGmyh095O8e4/qsz5Cx19cS/r+/aR3qDUQWtLKgtdexeC3fkOxX+U7qTt/BU3XbaTv33+Fm1JrvOXm8wivaKfvK79GVtSms+C1V4EmGPr2/SAlwjRY9JYbseojJ8UwTr/x/x+gcnl+Sm8plfNXqQy7yPFFRvB9CEyqgOUZVL6236ACaIdQL0pz9XMQ9QJp1fL/Ahwk6ymyizznEaFcnq9emNvnDHmeYgDlOWWViromlueEZymX1bvhuvPLLHu+81S5zGxYgDOFipMZyunC7Gev5FBOFyiMp3mEDP/JGDINobv24gGjwAtRudjKKC8ZB/WSFFAZMAxq2H8dSdGXLCfHEYqs9ENk+6dwCzUvVK9QoTCSJHNkfLasNJnFzRTniaRyx8eRvk++ryb3zx4fp5LIzTKLmXp60FbMAkBKcr0TRJe3PT+gPQ/kuz758QK54VowSidfoZSokBvJcBfTfJdpxAQEfq3ej27gBlTSWge17kso76UyauMChb2Gipea9n0Wk+ZK6mh3bXKDWbJ9NVGTkylRSvlkjtdyWuSHUlR8m+wc/Uq+b5qKa80yC4DiQBJ7uTPLLABKg2m8klAvBIDnUxrNY3bNjcN0eskvO1SSWcojNRGlm8rhFSuUR6b5CZPcThIxcITAgGLKO1BB4R9HfQ6h9qIIionY1Na8DXxdSsalZCkJrqKOWBkq4ynKAzX9lJvM4eaKFAcmZ8uKA5MqnM2cesXBSdx0YZZZzNQzosFZZjFTJjRtVnwuHZfyaBKrfo5f2QnQGa/DCAbVz4wPiq4p57thvchXGWErsBaVTdtExQxYjGIKe1BJJ+tQ6dENVI6xF1FjJP9U/d4q4OdMIZGqz0CtT63aZ2hOcirTVNYQwTmbvPqOmFcWCtbGPFsvBLalbilzn/OMIiEId9QTXViLsmtGAwQaIhyO+nyHMa5FZXO+AXWi2oIyfI+iNrA/pYa9iZqjF6AYh48yfg+i5ut2Emi2Qd2qdurXL0RUlaVWfZjIoiYaz61tKpElTZh1Ieo3LJotq9uwCKFp1K2r1avfsAi7KUawo372merWdxFZ2oIRrVr9mDrxNZ3PI3DPnfSASai1ntiilll9hV0fxopHeCxc5idMcwsqvc4LUWv9XFSOthagF5VoNQYUUdhfj5onEzUfP6SWx/BOEhghi9jSDurXdjETRTDYFifUHqdx8+LZsdWd04Fum9Sft3S2LLphMXrYxl5WMy4Ir12M1d6I0VC1INQEwTVdBJZ3IKoWcSJgEVjW8Twi99xJjwaxm+MEl9aexW5rQA/Z3BEq8GuSvBy1rl+MWuvrUQfSpSjX8gtR+8vMDeNm4FoU9qPA3SjcY8A9JNGiQeyORkKrOmrz3dGAEQsRWVMz4oisWYAQYn7Z6gWY9WHstvpa2aoFBBY0oUeUqZwwdMIrOggtb0dUY0fp4QDBhTXDjxOlM/qGYRjKXR+guUmJecIRyOHz99lBmlCh1hpQE/FllOE11bJ/Q4Wz/CxqQ3tNtQ6oVCWvBj6GSjj5KBClwqFojsV2bH6fYeUNbBjQ1Cgpl5XJnKYJ4jEQSDyvli+goZ7Z8Ax1cTX+piZJJqMidkYjqqylWZLLKWYSCJxeb+Onkx0LYsdC2LEQC68+h8JomoY1nUw5JT7avZ2VqCzQNsob6rsoRgy1XHofR13PJSot0ieq/18FvAcV6KcL6AFMiqSuX0qoLY6wTVb/1VWkukdovXQlZtim5cLlysxzJEXnTRuoaBoLXrwFLWAhKw7tN54LwJLXXcHor3djRAK0Xa0S1ax403WM3b+f0MJG6jcuVmVvvo7pbUeIr11IaEHjKcXyZMgIWCy+YSNmyMZc3MyCy9ZQnMrSuG4hA7kM/9Z/gEtQWbeXoMyEfkktFdXrUMzgo6j5KKGycL+7+v924NPV/4MK5D9FDuf6ZVhBibU4zrKXbqQwnKTj2vVovkPHJUvArVBJFVlw3SpkscCiP90ChoYvoOWaDVAs0Pyaq0jctwe7IUboghVIoOn115F78jD24laspcqDuel111Lc10tw/RK0hjAez84R5vkmPWjT8sKL0GyL6DmLQYKTzBLbsoqeqXF+ONbDrSg870elPNqFSmALinn/qvr/t6MY9xeA11b/HwW+jXovBlCb732keOELX4geDhBe14UvNJzRJPWXrUdo0HTVeoSlI8suDZer+Iptf7KV6YYIesCi4ZI1AHS+8jISjx/GbqsnWj00db7qCjJ7egkvayPQoXRFHa+4jHzPCLFNi2cPTSdDZzTDcF2oVFRym8kpdZsqFGBbLMN61PXIQG1ajaiXYYY6UKfcnahTV475AYg7UBy/gvL4+TYqKevD2SJXh6IIUeszX4D2NkmlAlPVm2qpDG2tkmwOUilV5jgqXHQiqUICgArFXlen4sTMiq+EJByCiUkl2srmQNflGcU0ypki5UwBJ1dm8L6DICWZwSkeWGpwkfQJobCPoE5Kc8+JHShvqh2oORlABfaZ+/8w6jT2NuBHwC+QPPDLJ7l87Uo81+Pwf96PdH2mdw2w6YMvJrlvkKPfeQyAzPEJlr7vJQz9fDtj9+5T403kWfray+n99oOk9inZunR9Wq9ay5Gv3kNxJAlCoFsG4cUtHPmPu3GzJaYe62H1u14wqww/3eSWKvTdtYflt55PcSLD0MOHQEJuNMntrRWuROEXQzHiAPOxb0et9R0ozKeYj30n6mbRi9rYfgF8CXjgF0+xYfEiihMZjv14D0hJ8miSDe+5mYknjtL3s10A5AaTLH/z9fT/cBtTjyoLGy/v0XzzBUx/+9cU+8YpALoHkfVLGP3mPbjJLLnHD2H92XUY8QjT374Hv+RQ2HmUzje+CLMxdqrgPCnyimUm7nyc9j+9isLxERIP7AagMp7k/8IJrkHdoEMoRiv57T0nB2yv/t3H/LnpRKVP2oc6uN4FvA/Y89OHWPbmDkq9QyR+/hRIqAxO0fqaK5i6fx+Jhw4A4CRztL/0YsZ++iS5gyqUlnQ9Gi5dw/D/Pkx5TIkTNV0nuLiF4e89iJcrkd5xjIVvuAaEYOT7DyNdj+yBARa96YaTZhpnvEiqWIRiqWa56vlQdCRLURPyr6hT1GtR4O8EHgH+vvr/F6GuiC7wL6jr4H5U8JgmYCMqctlNwEMIGjB/q0/fV5t9oVgbl+Mohlasifir35HzygpFNea5uo5iAcqV+UHIinPaPiNISvIjSbKDU7NAONkSxVyRNSgrqK+hXpDXoDKe70Xpjv6x+vdrUadgF/gQ8BDqRPbXKDHKZcAx1On4EQT1nk6qe5TkviFk1bywksyT659ietfA7NByvVM4qQLJvTUzx9TefqTvk9pfq5fc2095KqOYRfWZUvsGyB2fwK2a1fqOR/rw06NKnF7ySg6F8TSZgalZBV45madULLEJdbP7Dophvxx4CypM6y9Q6ZMeRt0obNSB6G9QWaS3oXLslVCiwUOoZKFPAfUO5PoTpLvHZue7NJGhMDrF9J6+2bGle8ZV+Ik5ZblDA/ilCsW+mp4pf3iA8kQKd8a/xZfke4Yp9o3hl5SVo19yKPaNzY+zdprJyxapTKUpHh+dLSuPJXDKFbaiDpZ3oPaO24C/Qhlx/Aj43+r//glIo3RHb0PtSQ+jGPQE6n3ZhYpnsgeoL/mUR6YpdI/U5nskgZspkDs0NDuO3KEhFVhwbtnhIZxkfpZZAOS6hygNTeFVTaal65E/MkLh6CjSVZuOly9RHPy98Uefkc6cmfodZNvz5f9CwGXhMHcieDNKFKIBbSgLhVejMkInUZy+CNwL1GNytRHnLZrOZaiXRWDTh+BGoXEugkEsrib+jH1aFszxL0PXlchsbj3LUjoMe056bttWOgzDmF9mmfPfk7ntnCkUbI4Raq2b/awHTK5fsZLvCY13oE5JQZR472qUl9TLUEzkcdQL8wDQisVl9Z28LhDgatTNIoDNTk3jhYbJBgQ+AS4RMaKLmogub631GbIIddQTW1ErC7TEMGJBostqiurI0laEphFe3DJbFl3aitUQwaoPz6sXXtiIZlUnRAgiS2rfORNIM3QCjVFCrfHZMjNsc+Pq1fyX0Hg3ygKtjDLwWIuSp78GxQweqf7vcaCLAJubF/Knls2NqBtHjAD3CI0XGSZrEbQQZpMeVTqrRTW5thkNEmxpJrq0Fmgw3FmPbptE5mAfXNSKFrSxWupmywKLWrGa69BCgXll9oLmmjOorqnPZxBptonVEMXuqN04jfoIV68/l69W1/1nUDi+AyX6vhnFOIooxlBAMYSlBFjevpgXWRa3oN6LZkL8r6awX4dgAzFW2jGs1jrsrqZ5fRqRIMGuGj7BrmalI51TL7iwGSMewqgLz6tnt9UhLGNeWaCrpo8UpoHdXtN7nCid0Wa1K82A/GbHYgAKBUmxpPQJAVtwuFLia5PjZH2PpbbNtnKB5cCglKw2wnywtZ3jXoXBSoXGksVi01b6BiFw3ao+wQQ35LG3XMRwBSucEOGgIFyNCDrbZ6imY8jmJE5FxUgyTYGUqi3PV+ayM34Y6bSytHp6n4YJsahqq1Kp6TDCYVV2ppjVro43yB/e9qcApI6PUxhP07Cqg0BDhB1jI3zlwYcoOA4rO9t5eHCA1QKOuh4X17fzwRfcyMFUguFkiqaxIovq62lat1D5o5RzTB8eJdZVTyFksntymqBbYGmpnqZ1HdSf04mwTaZ29pHuGaP10hVEquKi0QcPUxxL03nDOpyGRox8kdF79uJXXNpv3IRuGXjFCiN37cYIB2i7Zj1CE5Sms4zff4BQZwPNF60EINc3wfS2Y8TP6ZxVlJ8JZrUrg1H57WtfSLhFMYtEzyil6SxN6xZgRUM8NNDPNx99lIrnsWrhAu7vP85aoXHYdbmpuYt333QtuycnGE9laJso09XcSGNVqV+czpI8PEikI0a2IcTBRIpQPssyJ0TTxuVEF6vNaWpPH/nhCTquPpdgSxzfKzD2SC+VdIHOa1cjIzF8oTHws+34QNNVmxCGjpsrMnH/Xqz6KHUXrQWgPJ4g+1Q3dlcL0Q3L1DiOj5A70Edk7WKCS5XQ5qIPvf+0Y78iGJdfveWV2E0K+8zeY7jpPLHzVmKEAvym+yD/9+iDeFKyZNFiHjl2mLWaxkHH5WVda3jVzTexs7ebdLnI4vEKHZ1txNZ24XoecjRJpnuY8OIWknUW3VOThNNlOlydyKZlhJubgArZvf04YynqLl2HZutYpk7ikUP4FYfGy9fN+mFMP3QALWDScMka5YeRypF4vBu7JU7decsBKA5PV3UY7URWqTWQ6xkmf2SU2MbFBBcoxvP/N2a1rltLgjOdqIqGStDWJlnk27zL70JKJcd9W4fHnkwZL6ux2LXJpAUrGwI05W2yBXVF1DWIRCSJhBIfAbQYOpcFIoyNQ9GBchFMU6WbnOmzVFL6CsdRoaKlhIoDrS2SfB5S1SC10leBDtOZmm+GEIppJJM1kZahSwIBmJ5W7eTyqk/LOnN0GE6uhFMo4xYqjDzaje94FCczLLn5XJaXTN5VaAMpiclm3vGyS9i24yB+zyRdCZupfYOs37yE+sPTpI4mGBcJzJBFfEkLA/d1kx/NMLVvlGU3rePK9gUcu307k6lJUvsH2fDuG/A8ydHvPoZXqJA9Ns76v72ZdM84vT/ahnR9StM5Fr7tZiYeOczIL5VsXUrJwlvOZ+jn25l8tBuEwIwEaNy6nP7/fZRsz2g1K2OUUGcDff/zCKWJNMndfax+dx2B5jNDju6WHIYfOsSyF51HKZFj9PEepOdTTuVZfMNG1pcs/qbUDhLqjQ7ectsFPPXkAV7cm6RjwiJxeIRzz1nAwP4psgPTjB1PYEVswm31DD98mFIiR7p3isU3rueK5g6OP7mdqUKCbG+SNX91DeVEjv47d1bnu8g5b7me6d0D9N+xA3yJmy/S9eorGLtrN9P37wVAt0wartjAxB1PkNvXB5rAjIUJrlzA1M8eoTw0hdh9FKsxjh4LMfF/D+Ol8xS6B+l804swomeGPblXKpP4zU5aX3IZpaFJko/uB1/i5Yo037SV8wsmy4tKaxGLLOb1r7qU/Q9s408GErQNOBR7hti4oJ3Eb/ZSHkow1TOJWRdGqwsxfu8enFSe7LExum67hJaGdgbuf4xSycHtmyb42usoD42R+NVOcH3cVIHml1xIescxpu9XejrpSVpuOJep+/aS2qbiielBm/h5yxi/czuFY2MIXcOsjxDoaGD8Z09SmcqQ3T9A159fC5pg/PZteIUyhd5xuv7yOvSZGG4nSGe8SKpQUErnGZ8Fx1UbeG5uRI4SBH2d5aUQSwggEGRz1UQic6J0ZHPgejVmAaqdclnpJED1U8irfmf6dKt95vO1Pme+M7f9XP63+8zlwPPkPP1HLqd8NirVPqWsKcnPFJK+T3ZgmtSxsdlQEcWpLMWpLMnukVkgMn2TxITOkpEKXVVr/8ThYXzXI3Wk6ichIXF4hFIiT35U+Rb4FY9EzzjZwQTllFLwOJki03sHmdrei1f1xcgPJckcm2D80Z5ZvUZy7yBOMs/kw7WwBpMPH0b6PpOP9VT7lEw82k1pPEO2R8mjfcdj+skjZHtGKU0oLu/mSiR3950iFJ8dVTJFciNJkkfGZkOw5EdTlNNFEoeHZ+XcyZ4RmgJBFg+W6KjmmEgcGsYtlMlWbfWlL0l0j1KYSFNKVMNTVDzSvVNVn5dqmI5UnvTRMaZ2983Od7Z3gsJokvEnjkM1NMjkU714ZYfJh2rJ7VJPHsYrlBSzAPAlme3dVEamKA9Vx1F2yO45RuHwAF5aLXYvnadwuKZzOhOoMpWmPJ4kd7Bv9pkLx0dx8yWy+/tm6+X299ISirB8IEcbljJMONCHmypQrobpkK5H9uAgpYEpnKqfhFcokzs2SrZnZFaX406kKQ1MkNvTB9U1XjwygpsukNp+dLbP9Pajyut+btmOoziJLIWqT5L0fDK7jlPsm6AyVX3XihWyBwbIHRzEq/rFONNZCsdrOqcTpefEMIQQnxZCHBZC7BVC/FQIUfc76vUJIfYJIXYLIbafTB+m+duJ459epmlKp2Ca8+sIIX6rTNfm6w5Ma75+Yaae+Qx9zi0T4rf7NIxn7nNmfE/vc27+pKf394foj4G9XR/CniP/F4aGFQ3MKzPCNrplYNfVTomBurA66UTnyK/rw5hhG21OILtAfVi1NQeHUFucUHvtUYShKV1KR63MjAUxIgGCc+oF2+sRmkagJTanrA4zHkQPWfPqBVri8wKzBU9SlnvKsRcCOz4fe90yMEPWvDI7HkJo2ryyQH0E3TYxgtacsjBWNIiYE1jQrgth18852QsINkUJttT0JnrAxK4LE2qtYWo3hNEsg8AczOzWejTbwojX2rNa6zHqowjTmFdmtdTX5lugPp8EnWrshaFjxsKYDbVn1sMB9ICJOeNTApgNMYSuYdRF5pRF0UM2mj3nmRujmPWReS+73RjFapyTOF3XMBuimE21PrWQjR6ysZtr82E1qyi/1tyyljhGJIg2Z76tljhmY3TeRme11M37HprAapozhhOk56TDEEJcj4oz7woh/hlASvm+Z6jXB2yRUp6UWn6lEZDf7FwMQC4nKVV1GMFgTXfguBCLKn+NGd2BL5UYyDAEnidJpZUvUryqY6g4kmxGpayY0TEUi0q8ZAdqfhK5vKRUVB7YoZDqM5tVN4NoFOyZPjMqTmE8Pr9P5Yeh+nQcNd55fZaqfVoQjZ6cDuNUY786Vi9/+LKXAzB9aJjiVIb6le2EW+vwPZ+pvQM4+RJNG7qwYyG8ssPE7j6QkuZNizECFpVcicndfRhBi+aNi9AMHSebZrp7lEhnnPiCJqRuUpwcITXgUreqleYtSxC2ydgj3WSOT9Jy0TLqVrYjPZ+hu/dTmsrSee1a/M42tFSOkV/vxnc8Om7YiBkLUknmGbl7D0bIpv2GjeiWQWFomvGHDhJsq6P1ynUITZA+NExix3GiK9tpukDJfE9Uh3EqsV8RiMpvXXEj0QWNKrjc/kHKqTyN5ywg2BjFdz0mdvfhlV1aNi3CDAdwixUmdvchdI2WTYvRLYNyKs/U/kHMaIDm9V0ITSM3miTVM0y4NULdig6EbpHp7SM/VaJ+7VLqV3eoWFVPHqE4Pk37FRuJdDXhlXOMPHAEJ1ui4+pVaE2NuBWfgZ89hY+g6ZpN6EGbynSGyQf2YcbD1F+2AWHoFPvHye7owe5sIr5V+QzkDvZRODRAaPVCImuXACeuwziV2C8PxuR/3PQygh1NSM8nvbMHL1sgtnklZl0Ev+yQeuqwMpU/fxV60MbNFkjv6EELWMS3rMKr5PHLZfK7B7CaYsTPXYrn+7h9k2SPjBDuaiJWjag8fbCf7HSG0IYlxBa2I/0yme3HcCbT1F+8Fj0WwBQw/eAB/IpL4xVrMSJB3GxR6TBsk8bL16JZBuXxFMknurGaYtRftAqhaeSPjZHd109wcQvxTQrn9J5eir3jRNYtIrJcidf+aDoMKeXdcz4+gbI0e97I85Q4R0qlF3BdJVIKBCQVR+kJZsRGTY1KbDSjOzCqG3M+XxMbWbZSYGezSnykaco727LUZl4qK1FTMCARQsWJcl3FlAIBieuqcczk7J1x4stm1WddV6lHC4U5fVoQCdf6FEJZW9l2tc+S+gkEJeZJpAo91di7hQpexcUtVZjc049bKOOVHELXxClOZpjaP4DveGimQfvW5WQGppk+OAxI7LowDas7SXaPkOwZRRgaobY6Ih31jO8cIHVsivTxBIGbwugxwchjQ+RH8+QGJqlb04HMlxn61V7KiTxOqkBsWSv5/imG79mPV6ig6Rqtr2kjfXCQiQcPIn2fQHOU1ivXMrXtKFOPdiNMnciSFurWLWTsvgMkth/DCNvEVnUSaI4xetcecsfHyfVNEF/diRk7cXv0U4m9V3aY3N1PuK2OcrrI1L4BvJKD9CULrziH3EiS6QNDSM9XDo2bFpM6Pk7i0DBCE4SaosSXtjJ9cIhkzyiaZRBpryfYFGVqbz+54ST58TSh9gZ0WzCxe5RSskRpukRsSQuVTIGxR7pxciV8X2fln11B5vgkI/cfxK+4GCGTthc2ktx1nOTjh0FAoKOB+OYVpJ88TH5HD8I2CS5uI7ColfTDeyl0D1I8NkxoeSd6OEDq/t1UxhJUxhKElnWinYQc/VRi75cqZHb0EGhroDyRJLP7KLLiIkyDhss2UOgbI7vvOEiJVR8hun4puUMD5A70IQydQHsjelOAzI7jFLpH0UOWsmyKBJh+6gilsSSl8RShrmak55N66ihupohMF4m+vIXKeJLMI4fwixU0zaDh+o3kj46RelLpscz6CA0Xryazp4/09qMIXSO4oJHI6gUkn+gms7sXLWgRWtqK1Rwn8fABiv2TFAcmCS9rU1n7HjqIk8jiJHOEFregGfofBmYOPZ86jD9HOTo+E0ngbiHEjmoO3d9JQog3CiG2CyG2Z/DI5dWmPxOLqVxWPgvZTI1Z5PNKOZ6uhd4hlVL6hBmFNMwwgJqOwfcVgymVanGiXE9t9nP7rFSqfc5hUIWC0mGkM3MSvmeeuU/PUw5+oOpmsuo5SlVdiufBc4zw/Lxjn/YqpHsnSBwewa3KPbOD0xQm00zu7Z+Vc08fGMQtO0zs6q0mnoLxnb34rsfkHuUnIV2fyT39lBI5UsfUgc/JlZk8OE6mb5r8qJLvFsczTO3oY+zRHsoJVZY6NEKmZ4zhew7M6jXGHurGSeYY+VU1zLqE4V/sQvo+o7+qKsEdj9G7dlMcT5HYfgwAN19m/IEDpA8Nk6vKb8sTGaa21WTCz4KeM/Zzcc/iUZhIkx1KMH1wEK8q504fG6eUyjO5p39WrzGxqw/pSyZ29qrOfMnErj6cQpnE4REA/IrL1L5B8mMpcsPKVt/JVUj2jJM+Pk4pqRZhfiRJqnuYiW1Hcar2+4k9/eRHEozcd2g29tbwveq0O/KLHWq+fcn0b3bjFcskH1EOZrLskHp4H+WhSQrdysHMyxTIbDtE7kAflTEl46+MJcjt7302mM/Q8459aWCC8ug0mZ1HZmMxZfcexyuUSD91WIkvJKSePKRuIduVHk26Hukd3bipPIVupTPzChXSu5U+oVT1k6gkc2QOD5M+MIibUYrNSu8Epd5xMk8ewa+GH8/uPIqbzjP90IHZ+Z6+fx9SSqYfmFGC+0w/dIBKIktmt8LRL1ZIPt5N4djYbIBCJ5kjves4mT19OAm10RQHpsgfqfmanCj9QZGUEOJelJvD0+kDUsrbq3U+gAol9JJnSoMohOiUUg4LIVqAe4C3Sykf+oODE2ISmPHOakKZP58qOtXtn2gfi6SUzXAW+9PQ/mnH/mm4n8zYny2dKe2fxf70tT+L/R8kKeVz+gFej/IRCp1g/X8A/t+z6Gf7cx3r6Wz/VPRxFvvT1/5Z7M9ifyZic6rbf65WUjcC7wVeLKUs/I46YSFEdOZvVODM/c+l37N0FvvTSWexP310FvvTS89Vh/ElVBDGe6rma/8BIIToEELM5NttBR4RQuxBhbP5hZTy18+x37N0FvvTSWexP310FvvTSM/VSmr57ygfQYVYQUp5HBXj77nS156HNk5n+89rH2exP33tn8X+9LV/FvvT2/4ZHUvqLJ2ls3SWztKZQ2d8aJCzdJbO0lk6S2cGnbEM41SFABBC3CiE6BZCHBVCvP8Z/m8LIX5Q/f+TQojFJzHmhUKI+4UQB4UQB4QQ73yGOlcKIdLV8e4WQnz4RNv/Y9FZ7E8fncX+9NFZ7E+ATqVZ13M0CbseMKp//zPwz7+jXh/QdIJt6qicPUuppf0+52l13gr8R/XvVwA/OIkxtwObq39HUdlHn97+lcCdpxvfs9ifmT9nsT+L/ZmM/Rl7w5BS3i2lrPpa8wQqQdVzpQuAo1LK41LKCvB94Jan1bkFlVgL4MfANULMDRP4e8c8KqXcWf07i8rT1Pn7v3Xm0VnsTx+dxf700Vns/zCdsQzjafS8hL5AATk45/MQvw3ubJ3q4kmjUoafFFWvlecCTz7Dvy8SQuwRQvxKCLH2ZNv+I9NZ7E8fncX+9NFZ7J+BTmsCJXHiIQBcVDbWZ6JL5ZwQAEKIw/IEQl+cShJCRICfAO+SUmae9u+dKFf8nBDiZuBnwIo/8hDPYn8W++edzmJ/+uiPhf1pZRhSymt/3/+FEK8HXghcI6vCuGdoY7j6e0II8VPUFfB3Td4wsHDO5wXVsmeqMySEMIA4MP37n2TemE3UxH1XSvl/zzDezJy/fymE+HchRJM8yfDjz5XOYn8W+99R5yz2Z7H/3fR8KEJOxQ9wI3AQaP49dcJAdM7fjwE3/p76BnAcWEJNAbX2aXXexnwF1A9PYswC+G/gX39PnTZq/i8XAAMzn8+Un7PYn8X+LPZnsX/Gtk73JP2ehzyKkuvtrv7MANoB/LL699LqBOwBDqCulX+o3ZtRlgTHZuoDH0PFpgGVIvxH1f63AUtPYsyXouSbe+eM+2bgzcCbq3X+ujrWPSjF2sWnG+uz2J85P2exP4v9mYz9WU/vs3SWztJZOksnRP9fsZI6S2fpLJ2ls3Sa6TkzjP9/8fL8/yKdxf700VnsTx+dxf700fNhJeUCfyOl3ClUDPodQoh7pJQHn1bvYSnlC5+H/s5Sjc5if/roLPanj85if5roOTMMKeUoMFr9OyuEmPE0fPrknTRFhS7bdBNdB8+FampbAEwDhKbyas9Vw1im+l1xamWaAMOEoVA7fqXWiGYIhKEhXR/frTWiWRpCE/iOj/Sq5QJ0WyVM98qeUjOhxqBZOlKCX/Zm2xCGQDM0pCfxnTl9mhpCf1rbVNsWkEv0TskTTJd4KrE3zIhsbWgkZEGqAPlq/nEBtMTB0GEiDdXU3ugatNWpnOdj6dqchGyoD0PRkSSyNefVWMwgGNLJZV3y+RpujU0WhiFIJipUKqoRTYNYo43nQi5Vnm3bMDVCEQvP9clnK7NtBEIGlm1QKbmUiu5seThmoesahVwFtzonQkC0LgDA+HDPacfeMCPSshppiGnYpiCV8ymW5exYW+p1NAETSW/2fTANaIxreJ5gMlXDMhwQRCM6pYoklamVx+sMrIBBNu1QKs4pr7fRNEEmVcarrk1NF0RiNlJKsqnybF3T1gmGTFzHo5CrvWzBsIlp6ZSKDpVSre1I3ELTNPLZMl71XRMaRONnHvaNMYGpC5I5n3L10YSA1jq1fsdTcnYN2ibURXVcVzKdqb3nkaAgHNQoViSZXK28Lm5gmRrprEN5zrw2NZgIIZhKVPBn5tUUxGMaSJhK1LAMhnRCYYNyySOXra3vaMzEsjXyWZdSFXshoL7BRmiQSlRm51XXBXUNFgBD/UdOGPvn1Q/jRDwNgRFUusQDv6ONNwJvBGjC4IuxRcSiglRKkp7jjtLeBJYlGBuXlMsz34WFVZecwaHaphWwobVF8N4tH6A4lJ1tw2oMYjUEqSSLVKaKs+XBBVH0oElxJIuXn1kxEF5aj9AEuWNJlQwe0AIGoYUxvLJLcaA2QLM+gN0UwkmVKE/WEoMF2iMYEYvSWA53ziYXXlqH0DUe/u4r5+YUPmF6vrE3rQbe+vL3s6FLcOdOn6eOzcLAu24W1IUF/363z3halcdD8J4XaBQqkk//XM7Aw/ouuG2rxqHJMt9/wJzt6+rrWti4qY6HH5xk+7bkbPmfvX4RTc02P/jeACPDikvZAY3rX7OU7LTGg7cfQVYbb2qPsOmSBSQnC+x4cGC2jeXrm1m8qpHeQ1McO1AzNd9y1SLqGoPsemSQ6bE8AJomuPLWlWia4NPvvea0YP903Fevex8vuyrM0g6T2x/Jc7hfrUFNwNtvixGwNL78f2lyRYVDS73O628Okswb/OfPUrPtbl4V4NpL4hzoq/CL+2oY3/ziVhYsr+O+X41x9FB6tvzGlywjFDa5+/bj5DJqbYaiJhffsIxK2eWhO47O1m1fFGPt+R1MDGfZ+3jNrWDNeW10LqmjZ88EA0cSNRBuWEI4arPtN31kkmpeTVvnihcp/7EzCfs/u9qmvUHnhw+V6JtQu7epwztvDSKAf/1ZcfagtKhN4yWXRxlPeHzv3txsuxeeY3PRugB7Bh3ue7z2/r/4xmYWdAT49X1THO9Te46mwV+8uhPT1Pjm94YpllSf7S0mN1wfQSv7fONHtXlas76O8y9q4cjhNI8/ND5bfuV17XQtifLoA2Mc68lUnw9ue/VSgiGDn36/l2xGraVY3OTWly8B4N1/ed0JY/+8Kb1P0NNwI/BvKE/DZyQp5deklFuklFviQicaUeWxGAQCoOsQjytmAdBQD6apypsaQQiBEILGRlVmmaoOgB40MesDCF2gh03M6snSjAfQwyZCF5h1AfSg2tjsphCarSMMDbs1jNBUn4G2MMLQ0CwduyWk2rYNrMagajtkYNWrto2YjRGxVNtxGz2s2rYag2gBQ7XdEkboz34qTgX2sXCEdVV3oyvPESxuhlgQbtiomAXAi84TNEehIQJ/cr4qC1mCF54niAVhYSNcu06VL+/w2bRaIxzRWbk6yrr1cQDOv6CBRYtDhCM6F1/aSFOzDcDV17bS0GQRiRlcfVMLAJqusXZLO4GQQaw+wMoNqry+OcSilQ3YAYPmjggLl6kJX7iigab2CHbAYPGqRuoagwCs3NBCtM4mEDJYe0E7mnZCYXtOGfZzcbetCOetsljSrs5yV24K0NGkEw0JbtwaJGCpdfKCi0LURTQa4xo3XKCeqy6ic+XmEJGQRlerwYXrVfmaFUHWrQoQCWus3xBjxSr1Um3Y0kRza5BgyODcrS0EQ6rPjVtbCUVMQhGTzZepE5hlG6ze3IodNIg3Blm2Vh1ImzsidC6twwoYtC2M0b5Izevi1Y00tISwgwbL1zUTjqp5Xb25jXDMJhg2WXt++7PG/VRhf9Fqg/YGJUm4epNFS50gFhK84AILrbq3vOACi1hI0FInuP589T63NuhsPccmHBQsaTfYvEo978Y1AZYuChIO6WxcG2FBh9oXLtpSR0uTRSSsc9WlDZimmtdrLm8gGtVpqNO5/kqFZUNcZ/PWJkJhg7bOEOvPVVFDlq2MsWR5lGBIZ8XqOAsXq3ndtKWR5tYAobDBBZfU5vXiK1qJxU1icZOL/3/t/XecXFd9/48/z713+uzM9r7SatW75F7kKuOKK9WYGjAQQieEUAIJfAMpQEh+BAhgIAYTTDHGGBsbV9mWLFu9S7tale11dqffen5/nLszK2OCJSy8j0/2/XjsY++ePXPvndcp7/Pul7xYsPsfp5dFwjhdkYaaphiAegZEfIYRDk37AoZq9yQEguX2YEC1a7r6zBTpkQDS8dRm7W8UQhMY0QCupjb70vcyNPRoAOlK9FC5XQvqisEIpXYq39vAswNoQV0dB/1769GAUmlFA+Xvo2sY0QCe46GFp73gSdLpwj4UAM1/10gQ5jcIqmKSttpyn+o4zG9UaqjainJ7SxUsaFQMJh6eek9ob9KwjCitrRF0Xd07FNaY2x4lHjdoaY2U7pFIGrTNjVK0PKprg6R9iaWiKkRNQ4xAyCAUKY9JVX0Uy3RJVofR/TExDE31DepU1UVLfcPRADUNMWzLLalEToVOB/bBgGBuY3mexCIa7U0G2byksab8fWuSOvOaDHRdUFWhAepU2lJnMDoZoDqhE/EPVZommDcnBLqgfV60dO9QWKexJUY2Y1NdV8Y+nghQ1RBFExCvDOL4gnCyOkJNQ4xwNEAwbExhQHV9FM+VVNVHS8w3EFTYh6IBKmvL947EAtQ0qP7xxLSFfJJ0erCHtrryWkxEBfMadIoW1CXL67w+qTGvQScUgERMlFRIrXUG2bxHXaVO0B+qgCFoawkTDApamstzLRbVmdMaJpd3qaspb1zVVQHaWsIEDI/KhMGkr1qqa4oymbJIVgUJ+ocGTRM0t8b83+VxDUcMWtrUuNbWl5+ZSAZpbo2BgIpkWdo/GfqTGYZQb3kHsF9K+dU/0KcRGJJSSiHEOSjJ5o+Gvjsu5POSaFSQzUJqQrXn89DcJDEMwdi4+hugWISWZhWMODQMri82ei7U1IBnuRT7fZVUxkJogkAihJ02S2ojJ2MRnZtEC+qYo3mcSaXvcvM20fYkQgiK/Vk8S91cOh7hpjie41Hoy5RsGwhBsDKMk7Uwh3Ole0faEuhhA2u8gO2L5k7OItZeWWJgL5VOJ/apLBwZlsyrFzxzEB7do77Yvl7Jh69TksQ9z0m6BlX/gQnJuy4X2K7kzg2SnK8mtF3JlasEA2OCXz3hIGWafXvShCM68xfE2bF9gg1PqDV88ECGd7yrnXhFgEceGuLQQSXiD/cXWHfzXKSUbNvQg+nbJWzLZekZjeQyJjuf6UVKGDg2iR7QaJqTpP/oJAd3KJF9sCfN+VfOIxoPcnDHEP1HlYg/NpTjwmvmlxbbK419wZT8ckOOt10dp6HaYMOOIs8fUGB29dn85U0JDF3wyw05BsbUHEylXV5zWZh80eNnj2Ww7LJt7Ly1AY71Fvn179T33bOvwOve1EJVY5w928fYvU29Tu+xDFfd1EEwZLD1mUFGB9V6yGcs1l40F9fx2LbhOLZvA/Q8yYIVdUyOFdj9bD+gsA8GdWqb4hzvTNG5ewSA4Z40F1wzn1DYYN+WAUb61bhOjBc474p5J4W7j+tpwh5+8YzJO68MUxnXeGS7xZ5jCuNjwy7vvkYxvp8+ZTKRUxjnHcmrzgoxmfO496mcb1eyMXTByvlBDnSbPLlRfd+DXXlef1MDNVVBNm2ZYPc+1X6sp8Bb3tCMrgkeeGSU0TGlNsrnJRdeECGX93j0/h4cp2zzWL6qmr6eHM88oRbg4UNprrnRoK4hwq5tY+zertSBx49mec2bOggENDY8OsDQQMHH3uTKV0/PWPLS6OWQMC4E3gLsFkLs8Ns+BcwBkFJ+C3gt8JdCCAcoAG+ULzFi0PZNCHbZtoOUipkYBjjT2h2HqejHErOY/tnpxmegtOl7tntiu+0qQ7ZVbpeOp5iBKPcv5PuYHNgNPRaF9BBOvkBl9Rpq69eVPvti99bDRunZ6mUl0pMnzTA4zdiPZWFePYxmyt1NRxnAo0EYy0zr618XLErMYnr7eEac4JwwkVLH1tR42Y7jOJJMxiFeESA1XjakTk6oa9fxSswilz3Gni0P03tMMtLfy+R4nuras6muPZe8bxvKT7MRSU9SyNlE40Hy2XJ7Me/gebIk8ZwEnTbspYSJrEdDNYxPM1bnixLTkhgRcUL7eEbN61zBO4FZTPUZn5i2SICJlE1VI6QnyjjYlodpugRDRsl+AZSuLdMtMYtspoudm39H9yGH4d4+sukiNfUXUlW9toTtdIxdV2IWHEJh44T26eNzknTasHc9mMxLKuMwPm3eT+QkricR/vUUjfuG7kzOO8EpJ5Wdwn7aHiIhnXapqYKJyfKY5Asetu2hh/QT2qfGLZv3SswiPbmfZx7vZc92k+NH+8ikXeobLiFRuZxM2qauIXLCuFqmh1l0CQS0E9rTk9O8gk6CXg4vqadRttD/rc/Xga+f7L0FEIup63gMcjml/giFIORLcRUVMDZWvp46Kcbjkmy23A5KZaSFdDzTVTYFXyQOVIRwJk2kK9FCesmGEagM4xbUTYxECMfKkBrYhVOwcXOSo4fvRNUvGUJF3w+SzfyKdPoIyy97v/pcPIg9YSo1WFDHiPr3ToZx8zZI1We6auul0unE3tBhSbO6PqtDsL9PYjmwqAlqfDzPXyR4cLtE+tcAiYhgZZtkdw8YGpw9X7XPb/aorRSMTkjiFQaLFqubrFiZ5MC+DKbp0doWob5BidBrz6rkd78dQkpYdWYlmYkxDu7aidBzjA5OcvzIz4AG6BoDPgB0ks3cRyHfx4VXfxxQhtm+IxPYlkuiOlxSjbQtqGJyrICU0NpRiX4K9qPTiX1dpUZ7k5onaxeFODro4HqwvD1ALKLe9eylYZ7epSTUs5eoeVyT1JnXHOBIv00wIFi9QLUv6ojw3M4sk2mXqqoAHfNjSGDhskr6jmZxHElzW5xYXD1z/tIq9m5V0sGCFVVMpoY4fngHkgJD/f0M9D4A1AIZVBqk7WTSP8eeM8y6694HQEt7kqGeNI7tUV0fJZ5U7zJnYTX7t6pT8dyF1ScLDXB6sW+u1mipURifudBg8DkLT8IZCwx0/0B35gKDrV0OmoCzl6gttLFGp7lWp3/UJRwULGtXG9SyBSG27TXJFzxqqwO0NiscVi6N0z9YxHVhycIoYd8Dc82KCrbsSCMEnLU6xvDwAMPHD6JpYXqOdTI8sAGoBGzgPcBTZCZ/zPzF19LS9lYAFi2rpPd4DteVzJkXJxZX77hsVRVbNytpftnKqpOFBniFs9X+MTIMMAw1SMGgoK5WeUTFYtMYQ0wAEs8tMwZQhm7DUBtfLFq2J4Sa4jgZSzGPoBokLagTbq7AydsYFcHSSd+IBwk3xfBsiatP8Px9X8R154I3BIyiUsy0oTz8qoF/Ad5LeuLHWPYIUkuQmziOFg0TNBoJxEMl47YRCxBujOFZHkby1HW5p4uq4xAPKxzm1AreeL5kcBLOmFe2bZy7QBDUJa4HZ3SUP3v9mdBcBTUJWNDo61WDcNPlBgdGE8ydF6MioTan+oYwN9zczMBAkeXLE6WT/vIVSVwgl3epqRvjX/7uM9j2QqR3DFUuYC5q0xpCpff5IvB6RofvQ4r3kc8VGBvuZs7iGII6GtsSJcbQ0JoAoFiwaZt/apvW6aKKqODmi2OEAj6jbQlw40VRUmmPtYvK8+SCFSGiYYGhw8qOEBIHTRNcd0GM3YdNGqoNmusUxrGozmuvq6Srx2L+kioiUZ28Aw3NUS64rIXJlEn7omRpTXUsrsT2pa5gtJ/vffnvcd3FSO8wkAUWoPLu7QTOAr4AvIr+ngcxAn9JNjNOavwYc5fEEdTRPDdZsm20zKtEEwLH9WjtqPwzofrSqCIKN54fxPDn4NI2tT3mTcmajvJWeemqAJVxQTQkWD5Pp2CCoQuuPS/CgeM2LbUGtUm1t1QmdK59VS29/SYL5kVLxu32ORGuvLSGdMZh+ZLyxnXWmgShsEY46CLcQ/zzV/4d6S3G9Q6hBKXlKO3aXlSBwM8BZ3Ok65cEQ29nYnyEbLqXNWcnQFaxcGl5XJetqiIYUs9fsDh5ShjNaIZhO2BaklBQUChKhodVezYHTY0STRNMTkomfI+zogn1vjfx8IiyaYASiRMJgXQ9ir0ZpONhC4i0KPdZt+BQ6EuDBGeiSHRuEqFrWBNFLN+20dV5F67toVy9BWrDyqMKXDUDXwI+AnSAjDDes4dje34Jcj5S9lNZuYC5i95IbE4lWkBTdpMh37aRs4i0Jk5aj346aTQNY1lJTVywr1fy001KI7fzGLx7vcTQBb/d4bGpU/XvS0luPEvgScmdG6DX96i86SzJ2nmCdB7uesCmYI7x7KZx3vimOdTVhzh6JMe9v+hDStizc5Lb3jaXYFBj0zOjPLtR3eRI1zewTAnsRmE/HxgH0kAd8HHgHcA8pDTY8/wGNj7y3wixGMc5Qk3tGSxYegvnvWoegaDOsUPjdO5Sk2l8MM/ai05el3u6KJOX/OjhLG+/poKKqMbOLpPfblZ650M9NrddGUcIwQPP5tnTrdQKoxMel54RwHElP/ldhtFJFyHgxosrWDTfYCxl88NfjGPZkmefz/Gmt7URiOsc7UrzzCMDABzrTnPJ1XPRdcGerSMcOTgBwMG9X8Oxp7AHWIzyUg2hTrq3owrGtSPlBnY88xBPPfQ9EEtxnU4ami5i/tJXc+76dnRDo2vPCEcPKJXA5GiBFec2/1lwfSmUycNdj5u8/Yow4aBg80GbJ3crjI8Murx2nZJ+791kcnjAV0VZBmsXBjEtyU8fz5HOSTRhcsslMdrqDQZGHH75m3FcV7Jrb4bX39RINKKz50CWDRuVq/OR40VuvKYOIQSPbhins1vtOft2fsNXRe3x33A5qjpsAogCr0MdVtvx3J08/tv7ePBXdyK0ZTj2AZrbrubo4Su45qY5aJpg89PDHPLdqMfHLM69sP6kMZrxuaSKfnhEoRwmgeOA5avj8mUXZwoFZcPwPFliFgB5/7Nu0VW2CFDMwY+xcPJWyVgtXYlbVLpDd5q+NTfZA+RQZXPfh2IU3ahyuW9BZQ3+KErKSHFkx//gOVE8twfpfZ/JiRSTo9txi/4zp93bK7onBPHNBPIkdPsu3gf6ZcmWPzQJ44rPsX9aVv+p60yhzCwA9verTx4f1ij4tg3Hlhw7qm7S3ZUt2TYmJmzGRn0Db2fZp31ifADFnJPAZ1Gb11FgJQrzBcDfAN8CHDY8+F84dgzb6kd6P2V89ACjQ/tK/v/DfWXjy9hQDtc90bb1SlO+KOkbVXPwUE9Z19w36pIryt9r7+xV1+Npl9FJ3xlDQlePmmPH+sySbcM0PXqPqwXRe3Q6xmYpAG/geLk9nxsHTNQm9e+oZKjHUHFyXwSqgM8AdwMGj//mGzhOHMceQcp7GRrcxOhQdymwcmQa9tPHYaZQOi8ZmlDzobOvbH/oHvRwPbW3TDELgEPHVZ/hCZe0b9vwJBzp9xlNTzlYLl/wGBxW8/vIsfKG1j9oYpre77Wbpr/QiKJqOW1FzfsIaq4LlITxMBDl17/4Do4Tw7YySPlr+nt+y0BfP7msmkvHp413z7Trk6EZzzBCoRN/g3K3DfheYaHwiX2FEGiaIBj8/XtoobK7KyibBoAenuZipgk03ydOm+a2KTQDNUBhyiV5dVQm4W7gFtSgpoEA8AyqLsqPgLfieZdimiMl91x9+r396O+ZREJAq18kck5t+d2SEaj0PVTnTosNneO728bDUBOf3q4+21QtCRjlezc1K3vCdFfaaFSnqir4e+2aLlCLRgLX+60BlEh+BDUe3wYsVMmBXSjsvwq8FU9eiGOPltw4q2rLLrYVVeFTsmGcTgoY0FClVBpt9eV5Up3QiIYUnm115fYW/7oyrhOPlr9Lq//Z5oYgmt+s64KGJoVDfeM07OOBkr9+TX25HVyU6i9PGfsIcDkqnjcWWwAAT+VJREFUE/iVKEYy1d6Fwv7jwPsR4gw8b5yobx+pnIb9dHfbmULhANQmFFittWUsm6o0dE3tLc3V0zFW41ST0AgHy+uk2R+Tloby3hIwBLV+dHVTwzRX2kqDkK8qamqcrp62UJVax4Hr/LYKVEbzQZTt/2soRVESVeaiD3gT8HcIbSGaPkk0pt6xYdp41zecGvYzWiVlGBD29eixqEDUSiwbYlFKuu6qSsU8XmjDaKiHTEbFYEwZzjVDI9qWwM6Y6GEDI6YGzYgFCDfHcYsOgYoQmq9nDFZHlPqokAXNQcGVAr4DnI8a0O+j1CI/QInoDqr64Rn+m7wKCCO0e0nOvbVkNwlWRRC6SktiJEIzSh0FKq6iyU+FcFaHIBqSjEzCmnZB0Lcr3XCWoKVa4nlwlm/c1jXBX1wG27qVp8mqOaq9JiF507UBDo5VMGdOtMQQFi9NYAQ0RoaLLFmWIBxR+Fx6eT3J6iCjY2Ps2wWm66J0uHcA/4qS9n6IkuzuQtmQRoBzgUX+t3gdcDuaeIQzL/nbUtzG/BW1RCoCWEV3xunR4xF4y6uCVMVs8GzOWwoVEYPJnGTNfAMNEzy48UKd7V3KsWD1AgE4BA3JbVeG2NvtUJMULJoDeEUaq3Vuu6WS7l6bjiXVVNeFyDmSRSsqMQydzKRF+8LKUvzK2vMbiSSDFHKj7Nqm4zpp1GHpe8AnURvYT4BbUfFwVSiP1aspF5e7HfgrkL2cc9lrMAJqXBevbaCiMoTreLTOPzXD6+mieATefHmYmL/nXLIyQHWFIG/C2vnlrfJ1F4XYftghGoK1S1WcRjSs8cb1MQ4et2ms1ktOC3NbAtx4TR39gybz26MkKtR9zlqTpCJukM05LF8cL63/qy+vYfeBDNlMLzueDyPlGMpe9H1UQPog8CuUavAxFJOeAN4JTKmY3gP8E0LoXHvzh0oHonWXN1K/bxIELFp6ajaMmXW0egG5LiVxznEk4ymYnISJybL7bLEIqZRqy06TsjIZ1TaeopQ6REqJOZrHHlfpOjxfPeU5HuZIuX3q3l7RwRwpsHfj13GtPKoufARl7GvzfyzgURSUadTAHaZchXEfMER1zVJi+oJSWgu36GCO5rHGCtgT0/RnM4Qm82D6rnzDackD2+CxvfDk/rLq7GAfPLwTHt4Fe8qZOdh4SPLoXnhwO/SN++PnwuPPOTz7zDiPPTJcymE0MWHxxKPDbHpmnI1Pj5WwP3Y0xzNPDPOzH/wjZtEG3obC+CGgHeVBGQd+jFKXTALvQqlMpnRim4Ei9U3ryIzXlO6dGslzaMcwh/eM0Ns98TIj96dRtgCPbXeQUqJrMDTu8ehWh6d2uWw56KBrKm/XgeMuT+xweGy7Q3e/h4762bTb4uldNo9usZiYdNA9D7dg8uiGNM88m+PR342A5xHQBekJi+2bh9mzfYwDu8fQDNANGOzP0LlrkAd/9jlcx0CpXKcOR/NQTgaNwJeBBtS8fyvwNMooDvAIEKal7VpSw2U1wNhglkO7hunaM8LAsck/G64vhbIFeHK3XZonx4c9Https2GPzY7usrvrzm6HDXtsHt1pc3RQ7SFSSp7eXWTTXpPHthVJ58quzhs2pXh+e5pnnpvA9df/4LDJ089OsHlrml37yhvXwcN5Nj47xF0/+hJSVqAK8GVRNtL5KEYxB6UGbEAdol6PUktN+bM/BEDb3NfQc6R8ED3WnWXr5hG2PjvK8SP/D6qkpFQGblAMYCq2Ip8v2zAU81DXqYlyBcEpQ7iUlK7dglPKDSVtD3vSD5ybNJF+jIabt3HzanJYYwVcu0gx34k6Rf0IxcXfBjwFbAfORA1qtf+/W/zfZ6DE9UuAMA1NF57wfGu8AD4ztFPFEvOaKWQ5sKdHXW88KMn4PG1rdzku45E9EsdTOtvf7VZt2aLkmYOqb96Cpw74Ovc+jeOD6np0xGLfXhWIu33rBOm0wvvg/gxDQ2rSb3x6jEJ+AssaRmF7N0qS+xvUyWoPyvHggyhV1TKUPakOZdt4Fao0s6Su4XxG+rOkfAeGI/vHcH28D+8ZwZthNoyjgx5HeiWaK9i4x6Hgz/VN+1wKOdBcwePbHaRUcQNP7nQQnsbYhGDXYbVIsgV4br8HmsH+Ix79fk6k/r4iXQezGAL2bR8vMe6u/RMUsha6gL1bRynkh3AdE6Xq+CVKNfIV1MZ0EMWk/xHFLC5BrYMkyjD7KhSTMampP4eBY2ky/qHo8N5RPFcl75sK7JtJ1Nnv0juqsHpmn43l84kNe+ySDWPDHrWGbQee2qk69I+6dPWq68mcx87DatB2HzBJ+fEUPX1FenoVDlt2pDH9uJYtO9IlG8am5yfI5XrwPB11OP0tSnPxI+BBoBOlCv//oQ5Gr0XNfVDYr0fZ9Vyqas5g/54Jcr5tattzo3ieCrrc9typlVKf0SopUKcpUCk+plNZJzutr65sGFJKNI1SyP5UnxfaCaZcXIXxwnb1t+VM0HXg2yi7xQf8//4TqrriRtSAbUdx/X2ogZzSWT4C9AItCLEOTQ+d8CwxPe5CcCpBe6edoiGBi0Y0LJnyCtA1CAQ0XASxkMe4f1CJhcBFQzckAd0tJWebukc8cqJRPxzV8JBEYuUBFEKlCvGQuO4oXQf/E4X9h1E+//8GfAil+jiGkuRaUXrzJGqBRVDqkn7UKfhcNM3P3+Xbj4Kh8jMDQX1mYu8fymOh8rsFDUopJ2JhQcHP5jvVJxwU6Fo5q/OUaiUWOfH7Tem0p9R/oFS8wZAOmsRxhug68C2UPeivUZ4430QdlK4FDqBUI/0o9/JjKGmvHqWaHQGSCLEe0BBC4QwnYj/9eqaQACI+ntFwGbdIUJk/hRBEguXg1KlxioQEQkzP0uzf4wXYR/w4mug07IMBUQofcO1eug/dgWLIn0AxiB+i7HTXoCToHEq6M1E2vDNRe9DfoFTmGrrxFkCN65Qrbziik885petToRnNMHStbH9IVCgJw7YgHlepfwGqq5VKyvOgslL1FUJQX6ekDE2blnwwZBBqiOGkTbSwQcCPfzASITzbwys6GBUh9LBBITPIns3/hOckUIal2/23qgAeoGzYPg8ookTyH6MWWNzvfwOa/klqms4nnKhGjwfLiQ1rIiAl0vEIVEVm3KaVjMLKuSrG5YpVAtuFsYzk/EWaH7gnef2FGr/driJcr16jEQpIQgF4yyUaG/Z5JKOCa88QhAKS9ibJFRcYHOoL0NIWZvnKGEJ4nHNeErPgMDpqsWpNgppanWNHOnnykS9hWxUovflr/LfSUN5pE8DzKKOfiXKp/T5l28ZHgPUEAnfSvugGahqSNM1NloLHFq9tQGgC23TpWFY7o+xHoQBceaZBc62Gi+TSNQaOVO62FyzT0Qxwkdx8YYDHdyoV1eVrDDwk0bjGjReH2XrApjqhcd6qIFKTLJxvcFkuwtEem3mLkszriGC5kjMvrMa2PTKTFktXVhGLC44c2sW2TV/BdcLA/wCX+W9WQGG7H3VIWocyiL8T+C/UCfgwyovtfIzAt1m04rXUNMRo6agk7AesLjuriUM7h/FcjwUrX1JG7T8bBQ24co0gGbKwTbh0uYrsNi04f4nAsRSXuOEcwaYDklAQXrVGYJtFKkJwxVqD/cddapMay+d42GaRFfMMhsYiDI3azJ8bojbh4pp5zlsdxHMd8nmPtSsi4BTYvmMrO7d9B88zUNLEKv/NxlGOB4+g8L/Ab78OhX0VsAnFRFYQCHyTNWffRG19hOWrKgkEBNLzuOiyBrZuHkMIOOOcGqR38pL1jGYYLyQplfrDm35YlSA99b/pgf9Tf7+w/XW3VHHluggHu22+flca11VBNx/6SCNL5gd45JkCv3goy6Fn78TQimhhSbGYmPbABOpktR+1gR1CLar7Uafbi1GG74eJV99J8+L1JCvOwCs6L3hxwFPvfsILzhCqqTWwUWKCEdH41KebiSWDdO8YY6BTqZMaW4N8+c1NCA32bRgk7bvEnnVenFs/UEcha7P78QHsootlBHntbc3MmRdjcFSyeY+6t67Dx/66iaqEYP8Rj/2HLb7xH/+JwCQYFFjWC7HvRm1YYdTpah3wc9RpeB2QBXE/7Qt/znmXvw67uJiJUZNQ2KGyRp2uCjkHTXNBuETj5faZQHPnhrjt1loOb1N61Filzj9+vpFw3ODQcymGfbfLxQsjvOadNXiuZPeTo1ipAq4GV69P8pcfqSA3YbN7QwopBLomeN/tddQ0hBiZ0Njf6YAjqE8afOGzzcRjsHOfZM8hkx9/9z8QoohhSBxnOvYVKJvQVtQ4DFB2OADlBLIIof2SOQtGWH3+O7ALHeTTNrZr4aBUMbZn47gOniuxXJOZgzzMbQ/y6luSHNyp4iMqqw3+6a3NBMM6254aYqhXqTSXro3y5g81YJku258aZMjP6XXtTUk+sjLJ2LDJxseHsV0PYQj+6oMNNDUG6ezKs2On0rFHajQ+/4UWYlGN57Zk6Oqa5Ad3fR9Ny6NpBp43Hfs48BxKFViNYiCrUZJHERU82Yam/YQVq/s47+J3Mzoyl2zGQco8uj7FGBxc10YIECKHrk/L4fMSaUYzDNdT6UDicUiny0bt8XEIhySBgEo+OBVzMTICba3KjjEyUt6fU0BdHSyYY/CRtyvvgOULgvQNOfz8oTzXXx7lNVcpUSYZnuTLn/sMXv4IlZVgWQWKxQ+gFokEPkh9/TgdHR7PPhtCcfY5qEHsQHlIhdG0O1h43t8S0htLAXpWsYAWNjCiAczRQikWoziQJTavaka51oZjBlUL4vR3p1l1Xj1tSysBSDaE6R/IUsw7XHBVCzWNyk1yzTWtPHRXJ0ZA48xr2zB8MbhouWx9vI+G5jhnn6Xc2BpqIF306O73WLVAZ8k8JR6nU/286+8+QXqsj2QSHMfEst6JkjKywKdpbc1SVeWxe3cFSsqoQzHwBaiyCCMYxvd507s/zchAhC3blK52fHiE5tYI1XUhnntklH4/DmTTwwO87l0df1KK85eTjIBgxUU1DE9ajAyarLyohpZFyk/57Fc38KsfqSR0l7+6oZRxVAvX88T9xwgndNZeUYOmCaobQ2Rtj907crR2xOhYprBP1sBAymFiyObMlQEWtGtIKWlIdvOuL3wSxxohHgfPc5mcvA11gh0A/pWOjiLg0t0dQzGOCpQ6cDmKYezBMLLc9OYv0ncUeo5OAJBJmTQ0RYjGA+zaNsb4sFqw+zePcOmNc/5MyP5xCgQ0zr+ymd5jecZHTC5d38ychWrjvvymOfzg3w6o65vnlFyQEYJf/bSPqpogF13ZgBCChuYI4+MW2zePs3RhgrVr1Pg1NgbpH/UYHLK5cF2ChQsiSCmpqR7k3f/0KYRIE40qbUk6/VqUZqML+C5LlliMj7sMD9cDW1AHpu0o3C8BHicSEXzgLz/Ixs0mR7rUZvnkI5O8951xImGd3zw+zsiosmdsejzNW249+fTyM5phQFkf+0LpyXuRds8re09NP8xP3eOOT5x4kw+8Bj5wrQ0Rieu6vPc9/8xdd/2O1aslxSxMTChXXV0fobLyjSSTcOONae66C5qbQRmjpiZ8NdCObnyGUKiOucveTbxqLlbqBR5QvqH7BHFQqvcW/3t6nD87LasVzM24VE1L7azrGmc3SJysS2Kaz388onN+nYsWEiVmAdCU1Di/ziUSHkV52Cg6c4FkZatHOKpjmhZvefPf88ADm7jwQsnYsMI+HpcYRi9VVa8lmZTcckuab38bVqyA3bubUcwCVKR9HYbxfkLhei65+uMkks0c7zoxOWk+4xKv4IQqc7blYRZOKfngaaXWao24KamMl7E0DI15NeBYknB4GvZRjfZKQahanMD4apKCjjqX+qoTJdh5jRrxMNRXCrLZPK977Sd55pldXH215Le/VQezaNRB17uoqbmBqirJzTfn+MY3YNUq6O5eiGIWoBh1BCPwDsLhOi6+7jOE4/XY5nDpeVKCY2lIz8C2yu9iWx7Sm1lbkBCChqiLoReJT7M/BEMaDUYRCaWYCVD2oXq9SE1UO0G1WR2V1OtFqsMnJvlrijqIgEkyDOPjaW684a/ZtauT171O8pOfKIeeUMjCMHZRU/Nqams9rr++wH/+J8ybB8PDq1HMAmAN4BII3EY4WsfNr/s4k45GaloFRNeF/lSBaEwnN23eZwsuA+kCJ0svi5eUEOJqIcRBIUSXEOJvX+T/ISHE3f7/N/tVsl7CfSkVUKqooBT4FYtRCsyrqiwbwKurygWUqipVm6ZRusYxYSp60rGgqCJNv/rVn5CIX8nvfvcwmibZtk1Fjbuumuw33QSGkeY730lzww2waBE8/TSoBGB3oySPR9H0Yyxd+WGWrHkf1fOU/jGQCKH5tQP0aADdD2AKVkdKBvBgdeSUkg8qjE4P9p7tkT+uRPPM/iGcrKnKdB4YLklGEzv68WwXz/FIbVduxJ7pMLl7AOlJnLxFeo9KNFc8PoSd8iN7bY+oKUlKwZc+912qq65mx46NSCl5/HEVye+6Kr7m2mslicQk3/lOmmuugblzYfNmgGGUB4kE7sEI5Fi2+q85+8L3c8Y5Z2EXdOZ2VJOsVHaL1vYElZVx7ILO0pX1BEM6QsDKM+vxrAB24eSNgKcL++JQjmQ6y9yohzwyjltUbrbZQ2O0GA5zox75A6NI18NzPIqHxpgTcWnCIt+TRkqJm7cIDGaYn4BELoeb9dUPlkdrRLKq3uEfP/01Guqvo69vJ7Yt+eUv1Xx3XbXGrrzSpaUlzbe+leGqq1SJgB07QBm9n/Gx/y7BUIQVa/6Gs9a9n8Url+M5Gm0LqkvBeq0dlUTiERxHY8GKenRDQ9MEi1Y34DgajnPyc/90YT98cILApEdjRZTBLaPYBaU+O/rMEA3xKI3xKEefHsJzJXbRYeD5MRoTMQJZweBBhX1u3GTyUI7GRIxcd4qMn215tN9EKwjqEgZ/9b4v0dZ6A/n8ISxL8oMfqP3OcZRd9qKLbJYsmeTrX1fYh8Nw6BAo1+UdPvZfJhptY8Xaj7Pukr9k0ZIl2GacJUtriUbV/F66LEnASGKbcVavqUXXlYF99ZpabDOObcb/EBQvSi9HPQwd+E+UL10v8LwQ4r4XFGR/J5CSUi4QQrwR+GfgDX/s3rpO6cRkGILKSj/5YLycfDAUgmRCSRfRchApsZhq0zROiPqmkFYFwh0LpMevHtjKf3z7Hs4732XzZt9TJ6Q2pi9/GY4ehb/+a7WIvvAFeNvb1KIpFgOoDeuNwNsBwdJ1HyESrsUIBdD8QCWhC4I1EZy8pZIP+u+tBXWCNVE8y8U4xUIypxN7t2iX0pU4WYvJ3QMY8RC5o6lSn+JghsndgwgNiv3lgme5bhUH4ebtkusyUmL1jhIIRcBPFf+9u37L3ffey6pVHjt3+sWxwrB0qcJ6/3741KfUOH7lK3DDDXDwIFhWDBUwditKFajz2nd8Hs9tpLough7VcPAwohqL19aQGi3Q3J7A1ZW3V6IuyOLV1VimS1NHHEc7eePf6cLeM11yh1OlVDVOxiLbOY4eMk4oL2wO5ciGDIXrWDk/TqE3jbRdnFwer+iqg4gnsYbSGNkggYgKmPzqN37GExsfpr1d0tmpgmQDATjnHPjbv4UtW+Dzn1fr4T//Ey67DPr6wLbrgP8GbgIyCC3MzW/7/3DtGmoaokRiAC6BoM6i1TVkJkxa5iUIBNXptr4lxMJV1biuR3N7pNQ+E7C3cg7928pSaWawwPHNIxhhndFD5fk92plGD+m4pktmqIDyjoSeHSmKWZvsiImVV9/LsVyO7c+RqAowNqgOWt/7yY8ZGH6WmhrYu1fhbhhwxRXwV38FGzao+S4EfO97sGaNij+zrPmodCyXAgV0o4I3vPXzmGaSpuZoSUpOJAKsWFVFNmszr6NsC2lqjrBsRSUCaGx65SK9zwG6pJTdAEKIn6B8wKYP3o3A3/vXPwe+LoQQfyw/veNAoSiJhAW5nGTUH8tsFpqblRphPFW2bRSK0ORXHhwaLtfScFzfU0rTIdHAzt3d/MM/fJvJsXFcR3LtdRYHD6oN6/OfVzaTr3wFfvELuO02uPRSqKqCoSF43/sU83CcuSgvhi7gRwSjnyVotuIUTBxMQjJGIBHCzdsU/Zw5zoRJdI4qzmSnilhjSiR0MlapONNMwT5QESJQFcFOFYgvqKXqrFYA4gtqGfjNfqTjUXPuHKJzlQtaqL6C0Q3doAnq1y/AiCsmqEUCZPYNYSTjRJfPZdPm/fzTl75HPpMjnba46eYiDz6omP3nP68Wzj//Mzz0kGIQZ50Fy5fDrl3woQ+p+BvPW4byFOkF/p365u/TtSeC66SAFOdd3kBjW5T+4zmee1ypRo4cmGD9ja1EYgZ7to3RtU9tAAPHM1x+Q+vJ4n7asNdCOtXnNjP2dC9u3ia2oIq4nwY83FLB2FPHQULyjEZCfpoNIxkivb0XoQuqzmhSKXCoIts5jj2SR48FCXfU8uijW/m3r/4Qx7QZHJzkDW8y+eY3leTw2c+q9fKlL8HGjXDJJbB4MaxfD48+Cvffr7DXtDOQ8ipgGMTnaJ//OF27dDwvRfe+FJdf30pdY4TuA5PseEZh33s4zXVvmEswpLP5iSGOHFLrYWK4wPrrZw72wZjBilva2f7jw9h5h/YLG2herfLj1MyvYNdPjwCw7IY5xP30KZGaMIeeHiUQ0Vl7UyuG7yq873cDjBzOUtkcZ9n5lfzqV0/zzW/cTXbSoad3iI9/wuJzn4O2NvjkJ5WN9otfhIsuUpj/+Mdw663w05+qH8vSUVkMXge8FiE+xMLFnezcDlJOcnD/JFdc1UJlZZCDBybZtUMd7I52Z7n6ulYMQ+PZjSP096nDxdiYyYUXNZw08C+HSqoFlVRminr9thftI6V0UGG5NS/l5r4nG+a0WiueLDMDa5qh37LKyQdt+8R2APQAXd39XLH+A8xpe44rr+niWN9hvv99ePZZJT2sWQMLFihO/9RT6nR7/LjSH37iE+peLXPfTyJZjaYtQdMvRzc+zOJz3naC4cSbSmBoTq/8VP57KsEhqOJMp5h88LRiH6xWG1Kwpiy66ZGAKjn7gvapaz1klJgFQMi/R6Amwc5dh7n+1R9l8eKtXHbFAY73dfO1r0F3N7z3vYoxLF4Mt9+usLdtdaqdP18tKsuCjoUfIxY30bRlGMYlRGNf4vrXvBPXKeNnZm3qkgHMdHkSOLZEczzqkoGSigAgnbKpiunUnXzJytOGvdA19IiLZ2UwKsqqMiMWAAp4VqbkEg4QSAQBFy2s+czC71+hRGs9FuSpp3Zx6xs/zZo1O1l3yT56B/r4+79XJ9cPflDhvmIFvOUt6oRbLMLgoGr/xCfUaXfrtv9i1apB4vE1xOMXkUjcwfqrb8Xz572UYE4WqYlJstNsd2bRRbctamKSidFy+/iw6lsTO+m5f9qwN0I6ET+fWcW0fEvxughCA6FRYhaqXdkTolXBErMAqPDb43VR7rvvGd77ni9w3nm7WX/lflKT43zsY2o+f/Sjan6vXQuvf71SdWcyqsbP8uXwsY9BMKixeNnfEAptRNPOwDDOJVl5P2vOvKnkYOl5MJFSm+H4WHlTzOddin6Z1+nt069PhmaWxQkQQrwblTSFWgx8CZpoRAEJ6hQ6pWaKxcCa8PtEp2wYEInIUobb2NS+5pj87O7HuPRSi5tvVk3NzYo5LFmivKymaGxMLab3vhcSCbj4YmWIFUKjpnUFycol5HNHERGHyvY3EggmKPSkVSU9AXp8Kk9VEGu8CJ5E6KIUh2FUBEtR31rEmBEeUtOxn9NWT3FQAZ7vmSA6twqhCayxfMmGkT+WIrG8sXQN4BZsikMZwg0VSCnJ96h2c2CMH973NDfcYHKdn0ctmYTPfQ5aWmB0WuDp6KjarN79bqUaPOMM6OmBSCzM0tUriCfayWW7WbIiwsXrP4xhxOjcf5xM2sYwBHM7lF62fX6cPTsncB1JIhmgzi/OtGBRBUP9anLM7YhhnKL96OWiE3Cf04CTM8kfGcYr2uQ6Bwk1qNT3xYEJrKEJAPLdw8QXKy+XXNcg9sQ4djFLfHE1wcoY0vMo9o/hWgWcScEd3/0lt91mcuWV6pmGAV//urINTsd+ZEQx8NtvV9LdwoWwZw/U1tXQ3rGQzc99haef3s223UWS1Yux7SD79/SSz7mEQhrzF0QJBwVLl8Y5sDeN50FdXZCmxhCBgGDZ8gTPPKVUBUuXVZyQsO+VoBdiX5gwyfleXCOdaSp8L8CxrrRygQdGuyapXaC8LUcPK0k1O1IkP2ERrQziOR6jfjbY8eNpvv2dn3H77SaX+SEtlgU/+YlisGPT/DKGh2H3boX9tddCUxMcOQIN9c20tM0jHP0w+dxhlq+sZO2ZazGLOt2H+7Ftj3BYLyUUbJsTp683j5RQWxsi6nt0zZkb49DBtH99craLKXo5GEYf5YxjoEJv+/5An14hxFRqxTFehKSU30alHmVxICyD/oQKhwUNDcqGEY+VbRuJhED3i/hUTMOgtkapqlTyQTF1czQrf0L5VsdRTOdjH1OMwzTVRvbznyumNDqqpI6f/QwefChC24prCDclsCdNwvoKAhXlk164pUIFBUYMDJ8xaEGdSGsFbs4+obJeoCKE0ISyYSRPOfngacN+9cK50s35br/9aUaeOEygMkKue7QkSU3uHsRKF9E0jdyRck7zkSe7iS+oxU4XMAfVwvEKJu54lumClOModchHPqJ+JiaUPveee9TvfB7mzIG774b77gtx1WvfxoWXNNC1O0Y80UJ7Rznb5PWvaaXrUIbm1gh1fuH7+sYIr76llYG+AgsWVxDyT4DLVlUSierksg5LVyZPAu4XxXWKThn76bivmtcq+3/8HMLHKb9/mOzBEZUZwHJLfnSpJ7sY29iNkCAcUyWBcl2GHtyNRIBjEaioQA8ZOHoeL1PEneba77rqsPSOdyg70cCAkuh+/WslTViWsiXddRfc96sgf/nBd7F7r0ldrUG0chkt8wW69LBteNNbWzh0MMv8+VGqqgMI4TGvI8Lr3tjM4IDJilUV/gHP4/wLK0lW6Vimx+o1CYQ4pbQspwX7lUvmyz33HPXr3sDgrnGsrEUwGmBwb9l2d+jhPtJ9eay8Q+p4DtBxbcn2e3tpWFRBerBAxk9jnk8VyWe8E0pJu67SWFxzjVJDHT6sDqcPPzxVZlrtXXfeCffcE+Qdb3oLTQsaONCZprKyrcQYgkG4/IpGBgYKtLTGSoyhbU4MI9BAesKiY0FFaa9cc0YNyaQ6yM6bPy1T60nQy8EwngcWCiHmoQbpjaj8utPpPlRegU2o5CePvZT6urYDtq3iLUxLFVCSUm0kjQ0SIQSZrGTc36tsG2r8AmrjKRXDASCRfmU+wa1vu56vnnc/VVU5Wlrgjjvg5puhsVEZ9979bqVH/MpX4IEH4MEHYW77xURDSd70NzezcWMEcySHPeGLdK4kUBlGepLiQAavqCSMSGtC1e62XYp9GaQrsdMm0bYEQtdwshbFAbWZugWHcFP8VJjGacPeqFDeXV7RIVQfp/biDjRDI9KSYOSJwyChYkkdlWuUJkCPB0nvVh5RNRe0E21NIl2P0WeOUuxPI4IB3vXhN3DpFU8RjRapqYH/+i945zvV4vn3f1fS3LXXqnG480548kloa7uCcKiCD3/ybEINq3n6NyN0H8wiBFx2lWT+ogSW5fHgfX2kxixCIY3rX9tGVU2I8VGTB3/Vh2V6dB3McMPr2ggENDoPpHnyd4NICaMjJpe+qvFkcT9t2GePjrL1M/ey+qPrMaJBxnb1cfB7G5GepGZ1C0veeSEAR+/bRd8jKi6g/aaVtF42H4lkz39uZPLQCFpAZ/lHL6ZydSvIKO/7yJu4/ubt6LpJOAzf+hZ8/ONK7fEv/wLvf79SiXznO2ru79oFzS1XkYzF+Ld/OYv5K89k8UKDyqSO50k0XFLjMGo6/OIn/aRSDtuem+Qd72ylrjrI8eMF7vnZALYtOXI4x9vf1ophCJ59doIHHlSifD7tcPXVpxTtfVqwD8UNll4/hz33HMVzJHWLkyy4vBmhCWJ1YQ4/ropNdVzSROPyKqQnObxhkL4DWTRdsOraZirqwzimy877+siOmYQTQT7+iTfztrf/HbZt4nkK4y98QR1EP/1p+MxnlL3iBz9QzLuvT6O27koCMsz73n8mHY2L+cVDIwwNm+h6hksua6S2Lkwu5/DkE0MUCy6HOzOsv7KZcFhnoD/PM08N4XkwPFxk3cUqPmTvnhR7d08AUCi6LFteedLA/8myuK8ffD8qReJ+4KdSyr1CiM8LIW7wu90B1AghulCZsX7PDe4P0VSBpFyuHBBtWeUMtNMz1GazyoaRdh0Gc+4J7QAEQszpaOWpp7/F0aMr+NrX1P1TKThwQEkRmgZXX61EwUcegdWrO/jpT/+Br/7Hx1h39TUAZWYB2JPq2rNcxSxAFWdKq3Yna5XsE9L2cPJ+4rJ0+R5uzj4lG8bpxF5ogkiLOn3H5lWXJKNwQwWGL1XFF9SW+scX1CrsbRPLjx0Quka8Q6mNwy11rFi7gEcf+zo7dsznP/5DjeHYmML+xz9Wzgbr18POnfDcc3DllWv44Y8+w7/9+wc598JzsS2P7oNZ/7vD/j0qGnqov0BqTElDpulxuFOp0g4fymD5Sd3GR02GBpQaav+eydJc6tyfxjmFxI+nE/vicIaxbcdwUlkGNxwqZTge29lH/viYan+6q9R/YMNhnMkCx7YfY+CQYtqe7TL0WCfuaBo9EeX8i1dx/2++yhNPtPLNb6qT7OCg8kT74Q+hoQHWrVP2i85OeMMbL+H73/8k//qVv+K8Za0ErAyVftlRTRO01Lu4E2N07RkmlVLH52zW5cCuEazMGNu2jGD7RZuOHy/Sd2QYKzPGc8+VJdHnnp/AyoxhZV5U4H1FsI/XRYj7J/iG5VWllD31SytLNoyGZZWAWiMNSyuRUmIFTURUzSMjpFO/UJ3ga+dVcs115/CTu7/Er39dxx13KAmjrw/27VPzvrUVzjsP7rtPOda8+z03cscdf8tX//39dMxfwFjKYciXWFxXctTPNNvXmyvFFOVyDoMDfnLN7kwpPm2gv0DOzx81tS7Uddnr62ToZbFhSCkfQCVYmt722WnXRZR5/6RpqlDS1G9QIrNhlNunjNrCkHxxdIANhSwCWE6U99JMfCqQzLVBeixa1Majj32dr37p+3zxy3fxm984/OY3oGkasViUf/gHpcO8/NKV3HnX59XJ33VwpbqPFtLxTLd0rZ6tqcxl/kY0vV74dJrePmXDELo45VxSpxP74u7dOD3DmDU2sXlKdHPzRaxd2/FMC3NtNcZiFbg4eaSfd3/mX3j22BCepnHLTev47o8/g3nkKM7BHTiFBNJby+rVC9j07B184p1f5Du/eIS77/a4+26FfTwe5e8+U0ATgutedQbfu+sfALAzWfTxMWoJUhFXUiVAXcIklD1KbVCi6+VsxvXRSULZLHWx8qFB16EuMEwoK6hLOAz1q/ZkBcSK03KznwSdLuyFJgjFg7h5k3BV2bEgEA8h8HDzJpGaGNk+xTDdyhBv+ebd7B0axcLjEhLcRgORqhhkbeyBSaSUnHfecrbv+CG33/JZfvHYM/z3f3sIAZqmE42G+cynlHrx9bdcwn9++28A8AoOjqZhFwS25ZaSCGYzHjoGjdXeCUn3mmuDBDFoqgkwlW47FBTUJoIE0WisNRj1U2k01BoET3ELOl3Ye5aD3LqJUCqL2S2gaSkA5vAkwb3PAFAcaiLSqLwDj+/Yz4c+83l6JzOYt8NHPvw6Pv/P78Has4fwvi7sxDw4o5HLLz+DPXv+h5su/CAb9u/jW9/Cx94gFg3yqb8togmNt73xKv71X/9KPadnkIqRPrSCSdCoxnLUHtEYGKNyfJgWTWMHflJTJC30UjkuaQga9PpJUCNBSUO+k4AFNbEgfUU1fjVRi8rx6U5lL43ES9BOvGK0yAjL77e0l/7OZCW2pWwOIT8bpOdJ0hnlJXA/Y3Rlxvk1EgO4GcgYMb7Y1IIQggu2fRqMEISiKg6jVAIRCMYgEAQzrwL8piiSUMeKYob7xl/FVz73KJ7jYaeKoPmFkPzN3i06yoYR1E+wS9gZE6/goMcCpaJNUkrsiSLS9ghUhkuM5Km7bt0qpTzrtIH6EmlVW6O867KL1B8Cqq9YRaixktQTeyn2qBOhFglSe90ZCF3jk5/8L1J7O/mJ5+GgErt3XHYmH5/TAZ4kWudRcdZyIivmYw6MUegaKD0rtnwOgeoEuYO92MMT6pGGTsXa+YiATmZHN/1ujKFJj+FBk+ePxIgFXc5vzzBlrz46HmLfUITmhMWalnJcwva+GAPpAMsb88ytUicLx4WNxxLkLY3z5maojKgN7Kb/759ecewXRRLyzlddQ0Wbksyk6zGyqwc7W6R2ZRshv9yhU7AY3n4MoWt8M9VF8uhRvuN5ZIGLgNVtHXzmDdeghYNosSCxZY1E5tVijhcp9k8i7SKBaJj40la0SIBizxhetoim6xhVUUItlQhDxxpM0zPhkrFCREIe1W1JzKzNgYNFDMfBciWHjzkcOuowr9VgxUK1UUkpeW6XxUjKY+3SAC0NijGYluSprSa2I7nojBDxmBrA62578yuO/erF8+QP33M7mW5lr9ACGs3r52NEA/Q/1o3lp2gPVoZpvrwDJ2/zjg/+E2uPHuXLUjIKnCsEb3zLLVyZXAhAIOlQfeZSEq1xxg6mmDiqTvZCE7Sc20gwHqB/yxBF38MpEDNoObcB4TkMPD/KMRvCnk5nKsrOow41cYNV84zS3tLZ79A74tHeqDOvQe0hnpTsOOyQzktWthvUJKbS9Ei2dKpcUmcuCJQcDt7+6Xe8ZOxnnJfUdJrK3a5pAteV5HJKmpgKrgNl58jl4Elnkl8wRhBlAZOoHI4jTo7vjo1we61fjSoYVcxBD4CVV0cjIRQTMfybTjEMPaD6apqSTqbeq+DgZEwQAiMWRPcjuZ2shZ2xFMOIB8EQKuI5Y+EWHKQn0aMBlYLd9nDSFp7jIYI6wRdIIq80FYazeHoVQtOwc0We++ivMNMFale2Ub+6HYB0T4q9t/6A31lj3OsMEEGVdBEo7Hc9vpX61YK3nnkmrpZj179tZGzPL0kuaWLJB65CDxpYk3l23v5zcn3jNK1fzrw3nK/ufXiI5179bdyizfy3X4x2zhw8S1B5ZCsXP7AJLRYmfOvVGA1K8mnduoH6HYcwWusJvulqtHAQr2Cy7MnfsrhvhNAZiwm/WjFAZ3CUsx++F5kvEr3mAsJnLPmz4/uHyDFtxvcPEKlWNi1zMs/4/n4V+BkLUbOkGYBMzxjjB/q53x3jMXuIGCo5jeH/vqenm2Ubt3HzWavwTJPtn9xE+vAolSuaWfiO8xGegxfSCTXFMWJh7MkM1vAkWsggGKkmWFcBQuCkLFwvj5AatXVh6lojmPkgPT0OblriSXj9m2qpawkxPmSx66kUngfBsMaH/rqBeNLg+IEcXbuUGqWxMcAXvtSErgv2bZ5kuPfU3DtPB2U6Bzl251NUr1sBQLE/xeY3fwvPtKlat4L4YhUzknqui84v/5JfyhG2WcN0ovRfOlAjJV+98xdUXHUz5y9ajGc57Pubu7CODxFd2UHljesQQmANpdhy68/xMnkSrzqL+DlKkklvOcyxv/sBWkCn/tb10K484Q4PeBzskVRXuCxoNoiFwXElB3pcekddTEcyt15DE4JMXnKgVzGMRFSUGMbQhMfBXnU4aqvTmVN38nvOjC6g5Mmy/SGdUTpvKf1rPydNKgXPOVl+zhA/QxUvrEVlePo04AH35VM8lJ1UDCFS4RcFD0PY9xQIVUAwotrDFWXGEa0EI6AC/mLVaL5HR3E4h3RVanJzREkprukoqcOTeEWndBqx06ZSPU0xjqkCSmMF5YLrSayRPHKGFfFxLYeJbhV4NbzjGIXRDJ7lMLz1CFZG2QL6Nx3i8fwIDzkD/BqVJCUGLEFVrfCA7+7cwoaeY0wcnmD4+R7cgsX49mMMPakMtr2/2UG6cxA3b9H76+3kjisfz8M/fJricBo7XaDzO48DIG2H4j1PIvNF3JEJ8r/dCIDd3Ye5eQ/StLAP92Ju3gNAcdNunO4+pGlR3LQb+5iSavIPbsIbnUDmi+TufQLpnHy08WkjKZnoGiLbnwbNYGj7ccyJPK7lMLD5MK4tQTPo39jFb4rDPG8P8TBwJyrh/tkoS68A/mnjJrYPjzF+cIzUvkFc02Fs63HGtiqHouSaeQSr42ghg8q17ehxpbuPzq9GCxloQZ1wexJRzGMIi6alSQJBjXhlgIXLIjh2kfpmjeZ5EQJBjYa2ME1zA0i7yLylYarqggSCGvNXVRCNuki7yNKzKojGDUIRneXnJZF2EWnPkIqTUpLZ2Y05qOwsqWf24kzm8IoWY4/vQHqqONvYYzv4udlHtzXMEygXK4kKO78RlTf5Sw/dS/foMNltRzE7e5GmTW7LQcwuhf3kw8/jDKfwCiYT92/E8wPNUr/cgJct4qRyjP5Kze+RDGw64GI5MJjy2NKp9pADPS7dg6r9YK/L4QE1j589YDMyKTFteGqvTa6o9srHdlpki5JsUfL4zmmBbSdBM5phgDr8A7+Xlm/q70Fp8WMG+QIqyfjZwDdQJV0+h5I2FgBP5SYpGRimqKSOe6Fa7sXaJVK+yMv4L/iHPJx+r1m84PcMpil3vBNiRASlL3XcM7mHYb6Kiru+EPgqsBdVD6wGlR7t8a5OtBfEmUwZ0V+YQ6tc1GpaYaWpPkKoKjZTNFUZS3/BNC7d48XvfUJ/TXuRQXrlaUrNKbTyuwqVlxqAw7LAA4zyTdScvxz4AirT0E+BKCqP6SMHDv7e1xOeAzbIab6e0pO4to3EOzHbvgRXC4IwTlgOQgoihoGQJ2KsIQgYBsjyQ1W5WZ2AYZRiGdQzIWAYqv9MoheZJ0ITpTW7nwKPMcH3UPP7GlTponuAJ1HdLkay6ejhPzw3f28OTj3z9+f9C0O0SkXlXvzWJzxy2pQ5of2Fr/VSaYaN1ImkacpzBlTwnG2DZau2YFDQY1t81j5GAMnAtM8N+b/fhsrr+C/AcqSyW+QnIBTzkw/64ksxA0ZQ/Zh59T+AXEoNpNChMKH824FwYxxrJA8ahOtUWnQtqBOsjWBPKhtGsEqd1oxECLfo4BYcjFiwZMMI1kaRjkoeF6yOnDiBZgAZ4SCJeUqNV7+mHStdwEoXqF3RRjAeZv/YKF/IHSKALOENlMbh7aiSO/8OXOJ5JOdV0nLZfMb2jZJc3ET9RYsBaH31WvJ9KXK9SiUVbVEqpgXvuJjObz+Oa9p0vPlCbBQTCd96JfZvNyFiUWLXKRfTwNwmIpefhbmzE6OlnvC5SqUQPm8lTv8oTv8IoTWLMVpVKoTYdevIFi1kvkD0qvNnFPZC06hdPoe4j0Pj2R04BRM7Z1J/xjz0oMGWgX6+bB1FQ9W9myLfjs9bUGvgv4CbPKhaMoe63hTpIyNULWuleuVcEB4TW49hVCUw4gGyh0aRDkhdkNk5QHxFPULTyO0fAtPCwaDnuQFql9ViZiyOPD8OhSIjXTmONxjUzomRGigwuH8MJBzbahKLa8SqgvTsnaAwojx0DmwYYOnFDeiGxqGNw1A8+Yypp4uErlF51hJCdZUAVF+0grHHduAVLSovWI4QgqePdPFN2YOAE+Z9H0ol9SZU1Yr/AV7jeVSsnYs5WMTqHSayYh7hDqVSTF59Ll6uiJvJk7jiTDS/lGL16y5l4v6NaEGdulsuYgiojsPlqw22djlUV+ic5duJlrTpDIzr9Ix6zGso2zDOXxokUzBJ5yVnLwqUqv9duTbIY7vU3nb56ukJ9l46zWiGobijKF0Hg4CAoO8x9atMivdKyc9RmePzKJXI14AQSrJ4B+qke9fU6cixQbd8pjA9isxnEu70HCSeatd0lbDQJ83wUzBo4oTyrlrQQA+5yoBdOhQLtJABHiekbRCaQAsbCNv7PU+qmUDCKKdr1gIGkZoK9IBBqFIxyP/ZsY3PuC7/hipHP4RC8+soJr0CJZ4HUE7zAPHWJGYe4vPq0HwJQg8HiLfXIQI6sbbq0vODiSjxeXW4RZtwbYIpC5JWk0RvrkOLRdCm6mMCemMtxkgKo6UOpqSTgKH+RmI0lbNCiFgEo7kWL19Eqz7lwL3TQpqhE6kpR6DqoQCRmgqMSJBQQhm8f7RtC//muXwU5VvahSpgO1VM+HxUKSkTlQ9DaIJYUyWu5RBrqS55/Tljk2x5z50Uh9M0vWoplQtrQBNYoSDWeARNN7Ams8iChZSCzKhBaLSIOVmkmC9C0cLzYMe/Poq95wjGwlbC61YCYOc8nnnf3bhD44TOX0FgsYqzS3VO8ujXfo20HSJXn4NeO3PwF4ZOoLYc3ahHQgRrk3imTcDH/ifPPsX3PY83oRjzh1GHpJ+g5vqVfts4qNLLhk6gpRbpugSaym7oWjREoLkWLZPHqCljYFRWEGyuQQ9q6BXlFCS1FYL6SkF1XCuV6dWEoC6pYdpQX1ler6GA+jsclFTFy/tTPCKoTypvznj41KTqGc0wXBdyOUksJshkYUJ5EZLPQ0uzxJIedahqtm9GnWizKNH8y8CUZrQGCAoBmgEVtb6RO6ZkYjOnrmPKTY5gFCYHlZE7VgVhf/EGwjCmGEyhP4P0o0Gl4xFprsCzPYoDmTIP0gTBqjBO1lLSCMoorgV19LCBNZYvxXM4eZvYvMoZVabVzhbJ9o0Tb6lmdNcxRnYeA5SxddHrz8d0nJKt6DUohiFQdqNvUMa+DghpGtmBLAfv2gsSRjcfJlgZo/bsDvp+u4tjv3gOgLGtRzj7y28iVFNB5x2PM7ZFJXvLHB5izr++E+l5FL77K2RWnUqlaRO/5TKc4XGyP3lI2YN2H0ZEw4TPWIK5ZT/5324CwNp7hMoPvgG9ror8/U9hbj+ovmd3P1WfeOuMKdPqWjY9T+wjmIgSqa1gcMthxvcpvXe2L8XiN5xP0bGpQVXQfj+q7mAQVZj2e6h1AMoBISclE4d6OHr/DgDGd/cSTARIzEvQ93Anvb9TOKR29XHOl1+DURGi8qx2QrVq3uvxMEcf6iagC5Zc2Y4e1IEEGCGObxqmeKiX3A8fBsDa3kmwupLwqgVkH9tM4cHNqn33Eeo+fzt6Mk7qx7/B3HMYAK9nhNq/e8fpBfQkyDNtRh58nrZbLyGQjDH25E6ynUpuK/aPMvet6ynaCvsE8HmU+rUSlRr3TsrzvgnIBzUK+/qZfGALAIW9RwnU30CwuZrJ+zeTe1bZ8czDfTR/6g0IXWPsroew/fQvbrZI6F1XYeXgnk02ytRmEzEczluk0TUgeXyX2oc6+13q4w6tNYLH93ls6VQb0bFhl/ddpREKCH6+xaXPD4NJZ11uu/j/MaM3UAqpnx5aD8o18tJYkr9HlUD/D1Rx1OtR+vNBVC6Ax4CPI7g0nlT6wekbg2ac+Bt8PfmUbnxau6aj+/ka5LRArxLjcL0TBBZpKwOUZ59oUPVK7dMrP8lScNZMIiurpr+VKRslPcfFKVqsX7iIv0bV+voKcDXqdPUfKNVIFFWV+PNCcMXCxViT5gn4FEfS/u9yMJG0XcxU/vfap/piOSVmAeCmVLs3kT0x8eO4356aFpzkebiTfmR9atozMzmYSUZvnyz/e9rTsHdNG892ubBjAe9D4f1VlCS3DpXvexS1qO8FviY0XrV4Eda0JIwA5oSJIEhxfBqWRRs774Kuo0fL6W70aIiQHsAIaj6zUBSJq7XhjU2ecG931I8Nmd5uO3iTud9rd1/w2RlBnsQpYT8Nn2wR6Xqc2d7BXwBXodStr0PVebwDxSwKKHXUnULjsua5eKPTvqOUiJEJgqaNN1qem16uiJHOEzRtnFQ5EtkdTaOZDrm0d8IUnUhLMD0m0ic6ykxMemB6TGamJeK0oZD126dFEUzkAFO1nwzNaIYhUDEXoPJETRl5wmEIBeGMcJQ2PVQ6Vd2KWjy9qL3pfcDt6Lw+VscVsSTYJkx5ZHhOOQ7DzJZVTnax3KeQpmSlK6RLgXtT9gmAQLVSi2ghvZTFVegCw88malSEEIFywF/JhlEZLhnRjETwlAsonS4SukaiXaVtqF7aUtKxJtrrCCWjXNmxgHgowv+g1B63oCSNMdSkejPwYQJ8YPV5XNjaRrKjknirEr3D9Qnqz1d+6k2XL8OoUBhWrZpDxTz1zNZXry3ZFtpuPFO9UzhI4EJVmApDJ7JuDQCBec0Yc1V6Dy0RI+S7yYbOXIqo8FOAtzcTaFf648i6NSW1VXjdakRgZgnakdoKKlr8tNrL20rqu6pFTRiRILctX4mlB7gXpQ65HrgNyKGm1C3ApwjydxdcyurGRqoWNxGuUQsp0pCkerlyD226eAF6RM3H2vMWEK5X6phs5yhSKo+g3GEVc2PlHca71ebnWC69fnr4wMr5GK1qzPS6SsJnKeyjF61BxNQ6Ca0o94ldeU5pIceuPu/lhu5PpnBzNeFGpRqtXNNRetfk2vkIXePd51/EsNB5DDiMMnj/BUr95wLXAV8UYf7h8muZV11DckULRlJhH2qtJdKh3GQrL1iK8GvmJM5eVGLSVRcp+xuaoOYSdd2Y8FjUqJhAOABr56ouS5tgKq6zrgIW+JEDZ7ZTUlstb4bKqNpozp+v2sS065OlmbVSXkCGoQonAQQCgtpaiWUqJjKlQvhyUxv/PDTAmJ1DouwYAZQN4+/jbSwLRcrJBwGyY0rtZBcV0wDwXMiMKLWTVQ76wi5CZkxJHNOC/ALVYdCUgXIq+aAQgmB9FDdtoUUM9JCCVjM0Qo0xvJyDXhEoqZ30aIBQYxxpuwQSZV38TKFgRQQjpBhgtC5B2yXLKKayVC5qKmF/xy2v5e9+8wBD6XEkkgJKNRLQNL667ALmN9STnOtvJkGdxW85g9HuAlUr2ghWqUUUa6thyfuvJNM9TMO6xSUmUX/+QqTj4hQsmi5fzlRC1dDV5xFIxNGScYKL1coRAYPYa9dj7TpMYF4TerXa+PSaJBVvvAr76ADB1QtKnlfBpe3Eb7kcL5MrGchnCgWiIVovWVoqwBVvrqLl4iVYmQLVS1TeLk3T+O9bXstnHnyQ4ewkEkkeNefDusF/LF/H3NZqKuY0ARIjGmLeLWeS6R6lanU7RjQIjklFew0L3305hd4RGtav8sdVkj+WwnNs9ECQQk/5hNy/dYTJlENhLE962EUHtEiI5F9cj7mzk9CydvSEGtdAaz2V73w19vEhIueuKHl7hc9ZptxTTYvoRav/fMC+BDJiYerWrynNwVhHI/WXr8IpmCSWq7kWNAy+8frb+Mdf38tgPo2OOqyGgXgwzNdWXUJdawORZsXwA4kIDa+/iMKRQWLL55QOXtH5TdTfciFOKkvi7EWld6i8cBkyqBEOC5JrO8iiHAOvXQUNlR4tCY2GhFp/sZDgpjMkh4dhUQOEA6q9rVpw/WrJWA7WTEvRuHZu2Ttq9fTUjSeD0al97M9DtgOmKQmFBIWCZNhPP57JQnOTCuhz0hrvslt4F0ryaKhXoA0OScwsjGbBcSTJpFAeT8lGxQCkhPSwCtIzQpCoV+qoSAImBpRkEa4o2zZCUZhQl8WBbCmewrNdQrVRpCsp9mZK6qpwUxwjHsQtOhR7fdvGRJHonARaQMeeLGIO+7aNjEWkLTFj9OgA5kQecyJHqDLGRPcQvU+oNAITnYPMv/EsNEPH3NHL+9I1QA3J+Q20XaI2g8O/3kJxzzA9e4ZxL1hE9ZIWzEmTfT/chlOwOX7P86z57C3E59Uxtv0o+776IEjJ4KN7OeOLb8CIBjl697P0/HqbeuaeXuo++hoACnf8Gveo8sXyJjJELlqLl82T/q97kNkCBU0j8c4bCLQ3Y3f3kf7+feBJis/uovIDb0CLRSg8uY38w88CYB04SvJdN/3Z8f1DZOdNuu/fxvwbzyYYDzO2v4+BTYcASB8ZoePVZyI0gb21hw9n64F6apa10nTeQjzHpeve57F29XNkVz9zXqVRvbiewmiGgz98Bs926X/qECs/dDWRqiDDzx+j60fKfjTybDdr/+EmNF2QXNVErF3N+0BVhOFNAwgB869oJVIVBmo4+PQoI/tSuKMTTP7rXciCSfaBTdR8/DYCrfUUd3Qy8Z17QULh6Z3UfOrtaOEgmV8+Sf4R5QZhdfZQdfuNrwDKL05Orkj/Pc/Q+oaL0cNBUls6ST2nsC8cG6HphnMBCG7s4m/zjUAjVWcvpOrsRbhFm967N+BsOcLA1qM0vvpsom11FPpS9P34OXA9Jjbup+0vr8NIRJl49gBjDyrbRnbfcVredRVCCIZ+/jS5fSpVjTlagGvPwXLgv5+GVF7t9jefIVncKBhOS364URWw3NwN71gnqYwKdvZIHtytvtPePnj7hRJdE/x2N+zqVe0Dk3DNypPHaGbpQV6EilPaoWmxPa5bzh9VKJzYd6qA0lRywhM+awTL9gkhIOif7APhsm1D01U/UMF8UxQIYwilSJxiFtOvPcs9wbbh+kkG3YJd1t17slQ4yZl2D890kc5Ms2FIcoMTAGR7ysnhzMl8yaaRmdY+1ccpmBTHynrYqT7Z/ixOQX1nabtM7FUzN7XzeCkexhzNkPetcuO+kb3UB5AFs8QsAKyDqo/TN1K2bXgedqeqrWN1Hi/ZNmQmj9M/4n/uaOkezpF+pHWijv+VJtd0KPh2m0xPuVhFYTSDU7T89mmlRP3rKdfnUrsfBJk5Plq2nVkOmSMqIHNiXxnLfF+qNG7hhrKXVqjelxiiAZ9ZKKpuVWvDOdyHLPiLzXawDvqb3b7u0rx3Rydxh9S4mnu6S/eYfj1TyM2ZWL59IX9suNRe6FU11KXrUZg2JlN9rLE0bq5cjrhwXM213NEx8INyvbyJ2afGKn+onI3d7B3Fy/vp0DvL7dkD6no4q5HKlw+T3f7B+diYYhYApgM94yf+H1TQ35QZ7HD565xwfTI04xlGyJ+j4Wllr3WtnIwwPE2bEw75bqyaIBQ8sR1QLrLeVEZZqWwaoFRPpdJVrnK9nWqfIsfEkb4raLScCVH3c9BrQe0EF9upPlMFkwBVWMlPIzL9HlpQP+GzM4ME0QY/W21zVak1UBEm6Nsc4tPap/oYkSAhX92k+ih9cKwpVlLTCV0juVTZEyqXlwulBatiRP37VC4rl+6sXKb6iEgIrbW+/C7zVR+jqRYR8QdZCAIdqn+go6UcWBkNY/hujVOfAzDmNCCC08ZoBpAW0InUqiwE0zEOV8UwwsHfa5/CPlgRIRAvL4ipWI54a3VJzaIFdCrmKhySi8pYhhuShKvVuE1lLwCwRpUUbBdsipPlU1iqX60NY14zwlddYugEFypsp9SFAFpVBXq9eseQn6xSXZf7zBTSIkGCNQr7SGvZDTbcpDAUuka4uez+PdUnWF2BHilvUhHfBhWdU10KNtXCQUL+ZyMd5ZT6waYqNP+zkXnl9tgCdV0b90hEygfKub6HeFt1WcUU0KGl6sT/A1THwF+uzC1/HdqnXZ8Mzejkg4sDYfm95vbS34WCxLRUBb2Ar6+TUuWYmiqgNBWd7HmSTFYBGvd9kS/Y9mklQQRj4BTLsRfgB+75NgxvmktWMOrbMLLcl7qKr3zuUaQnsSeLCE3DSARLqiTXdnEyFvo04zaAU7D9wL1AadMEPymh7RFMhkoLeqYkH1xaWSPvfk052Wf6+AjFVI7qRc0YvqFUepLUoQGk51G1uBnN/w6OaZM62E8wESHZrjalSE0eV0QYO1KgankrFQvK9YRTu3vIdA9Tv24RYX+xSk8ytOEAbsGicf1yxoIV9KUFjEzibdqjjNury7pfZ3QCa89hjLmNBOeVmZDV3YdzfJDgygUn+LubOw4pG8Y5K0ob3tWf/vArjv2iWFL+6OobCFeWme7kkWFlw1jcjO6/q+d6jB/sQ9N1qhY2lWxjdt4k1TlAtDZGYl4TmiHRo1HyYykyR0apWjWHWHM1OCZaTGesc5JC3yiN61cRqjBA99ASCSKtFWhGgELPJMNZieVAJGgQ66iiMFZguNdBt23yroS+UcxdXQSXthP0cx8BmHu7sXuGiZy3Ar1SSS3SkxQ27UaaNtGLyg4H6993+yuO/cJ4pbzjpjcQ9I3UUkqyh/pwCxaJ5XPQ/Hf1bIf03uPo4SDxxS2l9W+l8+Q6+wg3VJUZScIjPeJSPDJEbNkcgnXlOZjZfRRnMkfirIXo/kHAs10mnj9AOCyoPGc5fZpO2NXpK8bYekzSXKHRUV8+XA5MSLpHYWE91CfK7QcHJeM5ZauI+kkGXU+y0y9su6atvFe+4e/f9/9G8kHHUfnfdV1g25Kx8bI6qq5WFVAqFFSxJCkBqarlgSqqPplWB0xdl0QiPpixaqVqch1IDymJQtMhXqvcaINhZdsAZduIV1NKhO+TPVnEGi2owBxdYMSDKif+SB43Z+PoAq1VRwvqKt/UUA5pe7g5i0hLAqEJ3IKtbBieBMcrif4zhexsEddy0IMGhbEsfU8fxC3aWBN5Wi9ZBsBk9xD9mw4BKoFjzVK1UQ9vO8L4/j60oEEgEiLakMS1XTrv3UnmaIrhZw6y6jM3E0xEyPenOPRfj2JN5Ml2D7P0Q1cjNMHY1iN0/fcGpOMiXY/gqy8AwHp8K9YT2yBooMWjBOa3Ih2X/H0bsA/3olUl0G+/CT0Zx01lyP3iMbyJDM6Rfireei1C17E6j5O99wmwHbVxXXHOK4Ty75OTN+l/+iDtV69GM3RygxP0PX0Az3Zx8hZN5ynvstTBfgY3dymJ2tCpnN+AlJLB5w4z2T2EHg7QkYgTa4jjFC2O/nonheE0qYODLH3PegwDsj0pDn//KZycSXE0z+J3rQMg0pqkcrWSAJHAgQkAGlfXUrOwEtt0KTw8RH7ARhYtMnc9hH10AGPLfqo/citaPIIzMMrkD3+Ll87h9A6TfOf1KpnijkOk735ELWQpia1/xc9GJXJzRcae2kvjtWchNI3C8RFGn9yNdDyk7VDlG6cndx4h9dwhhKGhhwNE2xuQnsfYhj0Ujo+gx8I033Q+gWQUO1Nk+JfP44xnyXcP0PyW9QhDp3B0iJFfb0aaNm6uSO1VyhMwveUQqYe2q7rusTis7EBK+N0e2NevEQvCG8+V1FUICpbkN7uUnbZrCG49VxI0BP0TyoZRtGEiX7ZV7OmD3/kZzQ0NVp2C4XtGq6QkkPWl40y2XO+gUAA/VxeT6bI2aWKSkjvgpO/mLCWla4xQ2S6hGxDydbWhWDnmIhBWPwCRZJlRRJPofvJBa6xQekHL92X3TLdkz5CuSl0OSoqYitXwii6OX/bU8hMVgirC5J1CEZ/TSZ7rMunrusf29eAW1XebODyEOaEGZXj7UQWwhOHtKsjOzpuM71e6V89yGNmtdNqT3RNkjqq00YX+CYafVgFjA4/swZpQao+xrUfI+s88fu8WFcsi4agf2CdNSzELAMuh8KS6to/0YR9WNhEvlcbcolaFuWUf3oSKubC7enB8+0fhyW3KowIoPLEFab8gyOcVpvzwJJlepZAe3X28ZH8Y29eLU1DzZ3jbEZDqxD6FvTmRZ7JbJaxwizajPvapA/0UhtUiyPWlGN+jjpn9jx/CySk10/BTBygMqT4Vi+sQmqrREl/kq/GiBjULK9V1SKd1hTqZWbsPY/u4OgNjFJ5X2Oee2I6XVvOkuO0gTq8a1+wDG1Xci4Ts/U+/vMC9DFQ4PkJxQM3T1Naukl0ytaVT2TA8j9TznYCKx0ptVYWsioMTJbuFmyuS3qvsa5O7+3DGlW2oeHSY/GGF1cTTe5GmWlOTG/fj+nag8cd2qnu7HiOP7gJgIK2xr18deHMWbD2q3nVfv2IWoIzYnX6ukueOKGYBsLMHJgtqn3nqkL9cJTzdeWr4zGiVlBAig0rN8uekWmD0j/Y6fc+cK6U8pbqVLyfNYv/KkBBiBBVS8Uri8Eo8cxb7V+6ZLxn7mc4wtvy59Zr/V575x+j/Cg6z2P/feuYfo/8rOJzqM2e0SmqWZmmWZmmWZg7NMoxZmqVZmqVZekk00xnGt2ef+YrR/xUcZrH/v/XMP0b/V3A4pWfOaBvGLM3SLM3SLM0cmukSxizN0izN0izNEJpRDEMI8a9CiANCiF1CiF8KISr/QL+jQojdQogdQogtp/isq4UQB4UQXUKIv32R/4eEEHf7/98shGg/ledMu1+bEOJxIcQ+IcReIcSHXqTPpUKISf977RBCfPZPeeZJvt8s9rPYz2I/i/3/jv1UoNtM+EHVhDH8638G/vkP9DsK1P4Jz9FR6ew7UBm5dwLLXtDnfcC3/Os3Anf/id+tCTjDv64ADr3IMy8F7p/Ffhb7WexnsZ+J2M8oCUNK+bCUcirs9lmg9X/r/yfQOUCXlLJbSmmhSvK+MM/yjcB/+9c/B9YLcer5x6WUA1LKbf51BtgPtPzvn/rz0Sz2rxzNYv/K0Sz2J0czimG8gP4CVeXzxUgCDwshtgoh3n0K924Beqb93cvvA1nq40+oSVR58D+ZfFFzLbD5Rf59vhBipxDiQSHE8pfjeadAs9jPYj+L/Yk0iz2vQPJBIcQjQOOL/OvTUspf+X0+DTjAXX/gNuuklH1CiHrgd0KIA1LKDafnjV9eEkLEgV8AH5ZSpl/w722oMP2sEOJaVGnmhS/js2exn8X+FaFZ7F85ejmx/7MzDCnlFf/b/4UQbwdeDayXvpLtRe7R5/8eFkL8EiXunczg9QHTczW2+m0v1qdXCGEASVTJ6lMmIUQANXB3SSnveeH/pw+mlPIBIcQ3hBC1UsqXJc/MLPaz2DOL/Yu939uZxf6lYf+nGFVe7h/gamAfUPe/9IkBFdOuNwJXn+RzDKAbmEfZALX8BX3+ihMNUD/9E7+bAO4Evva/9GmkHBtzDnB86u9Z7Gexn8V+FvtXGvvTPiAn+QW7UDq8Hf7PFHjNwAP+dYcP9k5gL0qsPJVnXYvyGjg8dQ/g88AN/nUY+Jn/Ts8BHX/id1uH0oPumvb9rgXeC7zX7/N+/zvtRBngLpjFfhb7WexnsZ8p2M9Ges/SLM3SLM3SS6KZ7CU1S7M0S7M0SzOIZhnGLM3SLM3SLL0kmmUYszRLszRLs/SSaJZhzNIszdIszdJLolmGMUuzNEuzNEsviWYZxizN0izN0iy9JJplGLM0S7M0S7P0kmiWYczSLM3SLM3SS6L/PxHGFhyBt69rAAAAAElFTkSuQmCC\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.colors import ListedColormap\n",
    "\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.ensemble import (RandomForestClassifier, ExtraTreesClassifier,\n",
    "                              AdaBoostClassifier)\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "# Parameters\n",
    "n_classes = 3\n",
    "n_estimators = 30\n",
    "cmap = plt.cm.RdYlBu\n",
    "plot_step = 0.02  # fine step width for decision surface contours\n",
    "plot_step_coarser = 0.5  # step widths for coarse classifier guesses\n",
    "RANDOM_SEED = 13  # fix the seed on each iteration\n",
    "\n",
    "# Load data\n",
    "iris = load_iris()\n",
    "\n",
    "plot_idx = 1\n",
    "\n",
    "models = [DecisionTreeClassifier(max_depth=None),\n",
    "          RandomForestClassifier(n_estimators=n_estimators),\n",
    "          ExtraTreesClassifier(n_estimators=n_estimators),\n",
    "          AdaBoostClassifier(DecisionTreeClassifier(max_depth=3),\n",
    "                             n_estimators=n_estimators)]\n",
    "\n",
    "for pair in ([0, 1], [0, 2], [2, 3]):\n",
    "    for model in models:\n",
    "        # We only take the two corresponding features\n",
    "        X = iris.data[:, pair]\n",
    "        y = iris.target\n",
    "\n",
    "        # Shuffle\n",
    "        idx = np.arange(X.shape[0])\n",
    "        np.random.seed(RANDOM_SEED)\n",
    "        np.random.shuffle(idx)\n",
    "        X = X[idx]\n",
    "        y = y[idx]\n",
    "\n",
    "        # Standardize\n",
    "        mean = X.mean(axis=0)\n",
    "        std = X.std(axis=0)\n",
    "        X = (X - mean) / std\n",
    "\n",
    "        # Train\n",
    "        model.fit(X, y)\n",
    "\n",
    "        scores = model.score(X, y)\n",
    "        # Create a title for each column and the console by using str() and\n",
    "        # slicing away useless parts of the string\n",
    "        model_title = str(type(model)).split(\".\")[-1][:-2][:-len(\"Classifier\")]\n",
    "\n",
    "        model_details = model_title\n",
    "        if hasattr(model, \"estimators_\"):\n",
    "            model_details += \" with {} estimators\".format(\n",
    "                len(model.estimators_))\n",
    "        print(model_details + \" with features\", pair,\n",
    "              \"has a score of\", scores)\n",
    "\n",
    "        plt.subplot(3, 4, plot_idx)\n",
    "        if plot_idx <= len(models):\n",
    "            # Add a title at the top of each column\n",
    "            plt.title(model_title, fontsize=9)\n",
    "\n",
    "        # Now plot the decision boundary using a fine mesh as input to a\n",
    "        # filled contour plot\n",
    "        x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n",
    "        y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n",
    "        xx, yy = np.meshgrid(np.arange(x_min, x_max, plot_step),\n",
    "                             np.arange(y_min, y_max, plot_step))\n",
    "\n",
    "        # Plot either a single DecisionTreeClassifier or alpha blend the\n",
    "        # decision surfaces of the ensemble of classifiers\n",
    "        if isinstance(model, DecisionTreeClassifier):\n",
    "            Z = model.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "            Z = Z.reshape(xx.shape)\n",
    "            cs = plt.contourf(xx, yy, Z, cmap=cmap)\n",
    "        else:\n",
    "            # Choose alpha blend level with respect to the number\n",
    "            # of estimators\n",
    "            # that are in use (noting that AdaBoost can use fewer estimators\n",
    "            # than its maximum if it achieves a good enough fit early on)\n",
    "            estimator_alpha = 1.0 / len(model.estimators_)\n",
    "            for tree in model.estimators_:\n",
    "                Z = tree.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "                Z = Z.reshape(xx.shape)\n",
    "                cs = plt.contourf(xx, yy, Z, alpha=estimator_alpha, cmap=cmap)\n",
    "\n",
    "        # Build a coarser grid to plot a set of ensemble classifications\n",
    "        # to show how these are different to what we see in the decision\n",
    "        # surfaces. These points are regularly space and do not have a\n",
    "        # black outline\n",
    "        xx_coarser, yy_coarser = np.meshgrid(\n",
    "            np.arange(x_min, x_max, plot_step_coarser),\n",
    "            np.arange(y_min, y_max, plot_step_coarser))\n",
    "        Z_points_coarser = model.predict(np.c_[xx_coarser.ravel(),\n",
    "                                         yy_coarser.ravel()]\n",
    "                                         ).reshape(xx_coarser.shape)\n",
    "        cs_points = plt.scatter(xx_coarser, yy_coarser, s=15,\n",
    "                                c=Z_points_coarser, cmap=cmap,\n",
    "                                edgecolors=\"none\")\n",
    "\n",
    "        # Plot the training points, these are clustered together and have a\n",
    "        # black outline\n",
    "        plt.scatter(X[:, 0], X[:, 1], c=y,\n",
    "                    cmap=ListedColormap(['r', 'y', 'b']),\n",
    "                    edgecolor='k', s=20)\n",
    "        plot_idx += 1  # move on to the next plot in sequence\n",
    "\n",
    "plt.suptitle(\"Classifiers on feature subsets of the Iris dataset\", fontsize=12)\n",
    "plt.axis(\"tight\")\n",
    "plt.tight_layout(h_pad=0.2, w_pad=0.2, pad=2.5)\n",
    "plt.show()"
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